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As engineers, we all dream of perfectly resilient systems — ones that scale perfectly, provide a great user experience, and never ever go down. What if we told you the key to building these kinds of resilient systems isn’t avoiding failures, but deliberately causing them? Welcome to the world of chaos engineering, where you stress test your systems by introducing chaos, i.e., failures, into a system under a controlled environment. In an era where downtime can cost millions and destroy reputations in minutes, the most innovative companies aren’t just waiting for disasters to happen — they’re causing them and learning from the resulting failures, so they can build immunity to chaos before it strikes in production.

Chaos engineering is useful for all kinds of systems, but particularly for cloud-based distributed ones. Modern architectures have evolved from monolithic to microservices-based systems, often comprising hundreds or thousands of services. These complex service dependencies introduce multiple points of failure, and it’s difficult if not impossible to predict all the possible failure modes through traditional testing methods. When these applications are deployed on the cloud, they are deployed across multiple availability zones and regions. This increases the likelihood of failure due to the highly distributed nature of cloud environments and the large number of services that coexist within them.

A common misconception is that cloud environments automatically provide application resiliency, eliminating the need for testing. Although cloud providers do offer various levels of resiliency and SLAs for their cloud products, these alone do not guarantee that your business applications are protected. If applications are not designed to be fault-tolerant or if they assume constant availability of cloud services, they will fail when a particular cloud service they depend on is not available.

In short, chaos engineering can take a team’s worst “what if?” scenarios and transform them into well-rehearsed responses. Chaos engineering isn’t about breaking systems — engineering chaotically, as it were — it’s about building teams that face production incidents with the calm confidence that only comes from having weathered that chaos before, albeit in controlled conditions.

Google Cloud’s Professional Service Organization (PSO) Enterprise Architecture team consults on and provides hands-on expertise on customers’ cloud transformation journeys, including application development, cloud migrations, and enterprise architecture. And when advising on designing resilient architecture for cloud environments, we routinely introduce the principles and practices of chaos engineering and Site Reliability Engineering (SRE) practices.

In this first blog post in a series, we explain the basics of chaos engineering — what it is and its core principles and elements. We then explore how chaos engineering is particularly helpful and important for teams running distributed applications in the cloud. Finally, we’ll talk about how to get started, and point you to further resources.

Understanding chaos engineering

Chaos engineering is a methodology invented by Netflix in 2010 when it created and popularized ‘Chaos Monkey’ to address the need to build more resilient and reliable systems in the face of increasing complexity in their AWS environment. Around the same time, Google introduced Disaster Resilience Testing, or DiRT, which enabled continuous and automated disaster readiness, response, and recovery of Google’s business, systems, and data. Here on Google Cloud’s PSO team, we offer various services to help customers implement DiRT as part of SRE practices. These offerings also include training on how to perform DiRT on applications and systems operating on Google Cloud. The central concept is straightforward: deliberately introduce controlled disruptions into a system to identify vulnerabilities, evaluate its resilience, and enhance its overall reliability.

As a proactive discipline, chaos engineering enables organizations to identify weaknesses in their systems before they lead to significant outages or failures, where a system includes not only the technology components but also the people and processes of an organization. By introducing controlled, real-world disruptions, chaos engineering helps test a system’s robustness, recoverability, and fault tolerance. This approach allows teams to uncover potential vulnerabilities, so that systems are better equipped to handle unexpected events and continue functioning smoothly under stress.

Principles and practices of chaos engineering

Chaos engineering is guided by a set of core principles about why it should be done, while practices define what needs to be done.

Below are the principles of chaos engineering:

1. Build a hypothesis around steady state: Prior to initiating any disruptive actions, you need to define what “normal” looks like for your system, commonly referred to as the “steady state hypothesis.”
2. Replicate real-world conditions: Chaos experiments should emulate realistic failure scenarios that the system might encounter in a production environment.
3. Run experiments in production: Chaos engineering is firmly rooted in the belief that only a production environment with real traffic and dependencies can provide an accurate picture of resiliency. This is what separates chaos engineering from traditional testing.
4. Automate experiments: Make resiliency testing part of a continuous ongoing process rather than a one-off test.
5. Determine the blast radius: Experiments should be meticulously designed to minimize adverse impacts on production systems. This requires categorizing applications and services in different tiers based on the impact the experiments can have on customers and other applications and services.

With these principles established, follow these practices when conducting a chaos engineering experiment:

1. Define steady state: Identifies the specific metrics (e.g., latency, throughput) that you will look at and establish a baseline for them.
2. Formulate a hypothesis: This is the practice of creating a single testable statement, for example, ‘By deleting this container pod, user login will not be affected’. Hypotheses are generally created by identifying customer user journeys and deriving test scenarios from them.
3. Use a controlled environment: While one chaos engineering principle states that experiments need to run in production, you should still start small and run your experiment in a non-production environment first, learn and adjust, and then gradually expand the scope to production environment.
4. Inject failures: This is the practice of causing disruption by injecting failures either directly into the system (e.g., deleting a VM, stopping a database instance) or indirectly by injecting failures in the environment (e.g. deleting a network route, adding a firewall rule).
5. Automate experimental execution: Automation is crucial for establishing chaos engineering as a repeatable and scalable practice. This includes using automated tools for fault injection (e.g., making it part of a CI/CD pipeline) and automated rollback mechanisms.
6. Derive actionable insights: The primary objective of using chaos engineering is to gain insights into system vulnerabilities, thereby enhancing resilience. This involves rigorous analysis of experimental results; identifying weaknesses and areas for improvement; and disseminating findings to relevant teams to inform subsequent experimental design and system enhancements.

In other words, chaos engineering isn’t about breaking things for the sake of it, but about building more resilient systems by understanding their limitations and addressing them proactively.

Elements of chaos engineering

Here are the core elements you’ll use in a chaos engineering experiment, derived from these five principles:

• Experiments: A chaos experiment constitutes a deliberate, pre-planned procedure wherein faults are introduced into a system to ascertain its response.
• Steady-state hypotheses: A steady-state hypothesis defines the baseline operational state, or “normal” behavior, of the system under evaluation.
• Actions: An action represents a specific operation executed upon the system being experimented on.
• Probes: A probe provides a mechanism for observing defined conditions within the system during experimentation.
• Rollbacks: An experiment may incorporate a sequence of actions designed to reverse any modifications implemented during the experiment.

Getting started with chaos engineering

Now that you have a good understanding of chaos engineering and why to use it in your cloud environment, the next step is to try it out for yourself in your own development environment.

There are multiple chaos engineering solutions in the market; some are paid products and some are open-source frameworks. To get started quickly, we recommend that you use Chaos Toolkit as your chaos engineering framework.

Chaos Toolkit is an open-source framework written in Python that provides a modular architecture where you can plug in other libraries (also known as ‘drivers’) to extend your chaos engineering experiments. For example, there are extension libraries for Google Cloud, Kubernetes, and many other technologies. Since Chaos Toolkit is a Python-based developer tool, you can begin by configuring your Python environment. You can find a good example of a Chaos Toolkit experiment and step-by-step explanation here.

Finally, to enable Google Cloud customers and engineers to introduce chaos testing in their applications, we’ve created a series of Google Cloud-specific chaos engineering recipes. Each recipe covers a specific scenario to introduce chaos in a particular Google Cloud service. For example, one recipe covers introducing chaos in an application/service running behind a Google Cloud internal or external application load balancer; another recipe covers simulating a network outage between an application running on Cloud Run and connecting to a Cloud SQL database by leveraging another Chaos Toolkit extension named ToxiProxy.

You can find a complete collection of recipes, including step-by-step instructions, scripts, and sample code, to learn how to introduce chaos engineering in your Google Cloud environment on GitHub. Then, stay tuned for subsequent posts, where we’ll talk about chaos engineering techniques, such as how to introduce faults into your Google Cloud environment.

As the Chief Security Officer for Google Public Sector, I’m constantly engaged in discussions about the evolving cybersecurity landscape, especially concerning public sector organizations. My colleague Sandra Joyce, VP of Google Threat Intelligence, recently highlighted in her Cloud CISO Perspectives blog “Our Big Sleep Agent Makes Big Leap” that the pace of innovation in AI and cybersecurity demands a proactive and integrated approach. At the recent Billington Cybersecurity Summit, Sandra further reinforced this message in her presentation, saying “we are on the front lines and the urgency is now.”

In light of this, I want to share some key insights around how we are acting with urgency and addressing a number of challenges.

Understanding the threat landscape

Recent headlines have highlighted several key vulnerabilities and attack vectors targeting public sector entities. It’s clear that legacy systems, misconfigured cloud environments, and the exploitation of known vulnerabilities remain significant concerns. Email phishing, supply chain attacks, and state-sponsored cyber espionage further compound these challenges.

Our unique approach to security

We believe that security is not just a feature, but a foundational principle. Our approach is built on several core tenets:

• AI-Powered Security: We leverage the power of AI and machine learning to enhance threat detection, automate security operations, and secure AI development. This intelligent approach helps us stay ahead of evolving threats, as Sandra Joyce elaborated on the transformative power of AI in cybersecurity.
• Secure by Design: We engineer security into every layer of our infrastructure and services, from custom-designed hardware to advanced encryption techniques.
• Zero Trust: Ensures that no user or device is inherently trusted, regardless of their location or network. Access is continuously authenticated and authorized based on identity, device health, and context.
• Shared Fate: We operate under a clear shared responsibility model, securing the underlying cloud infrastructure while providing tools and guidance for customers to manage their own security. We believe in a “shared fate” where our success is tied to your security. We are deeply invested in your mission’s success and security outcomes, aligning our goals with yours to ensure the resilience of critical government operations.

Our commitment to the public sector

The cyber posture of the federal government is a matter of national security. As the geopolitical landscape shifts and adversaries leverage advanced AI, legacy defenses—no matter how robust they once were—are now a liability against threats powered by machine learning.

We’re focused on supporting our customers across three key dimensions:

1. Modernizing security operations with an AI-native platform: The battle against AI-driven threats is won in real-time. Google Security Operations (FedRAMP High), an AI-enabled and threat intel-led platform, transforms the federal government’s security operations from a reactive, human-centric model to a proactive, intelligent one. It empowers federal analysts to stay ahead of sophisticated attacks, helping to ensure the continuity of government operations and the integrity of its mission.
2. Arming defenders with frontline threat intelligence: Static threat feeds are obsolete. Google Threat Intelligence offers a decisive advantage by fusing the trusted intelligence from VirusTotal and Mandiant with threat insights from Google. This is the same frontline insight that protects Google’s own infrastructure, giving federal teams the strategic edge needed to anticipate and neutralize threats. This unparalleled intelligence is seamlessly integrated into Google Security Operations, delivering immense value and capability in a single platform.
3. Enabling mission resilience with elite incident response: Even the best defenses can be tested. When a breach occurs, immediate access to expertise is critical. Mandiant brings decades of experience and unparalleled threat knowledge directly to the federal government. With our Incident Response and Expertise On-Demand (EOD) services, agencies can contain, eradicate, and recover from a crisis with the world’s most trusted experts at their side.

A comprehensive portfolio of solutions

We understand the critical nature of government and public service missions, which is why we offer a comprehensive portfolio of solutions—including Zero Trust architecture, advanced threat intelligence, and secure cloud infrastructure—all designed to help safeguard sensitive data, maintain operational continuity, and secure critical systems against both current and emerging threats.

The attack surface has fundamentally changed; we are no longer just defending networks; we are defending the entire ecosystem, from the complex digital supply chain to the millions of non-human identities foundational to modern cloud operations. Yesterday’s security models are insufficient for this new reality, and the only way to defend at the speed and scale required is through a proactive, intelligence-led, and AI-powered approach.

Partnering to secure your mission

Please join us at the Google Public Sector Summit – and my breakout session on “Unlocking the power of AI to secure critical infrastructure and ensure mission success” taking place on October 29, 2025 in Washington D.C.

AI is presenting a once-in-a-generation opportunity to transform how you work, how you run your business, and what you build for your customers. But the first wave of AI, while promising, has been stuck in silos, unable to orchestrate complex work across an entire organization.

True transformation requires a comprehensive platform that connects to your context, your workflows, and your people. That’s why today, we are proud to introduce Gemini Enterprise: the new front door for AI in the workplace.

Delivering this level of transformation requires a complete, full-stack approach to innovation, and this is where Google leads. Our advantage starts with reliable, purpose-built AI infrastructure, and is powered by the pioneering research of Google DeepMind, and our versatile Gemini family of models. Sundar talks more about our company-wide approach in his blog.

This complete, AI-optimized stack is why nine of the top 10 AI labs and nearly every AI unicorn already use Google Cloud. It’s why 65% of all our customers are using our AI products including: Banco BV, Behr, Box, DBS Bank, Deloitte, Deutsche Telekom, Fairprice Group, the US Department of Energy, and many more around the world. Today, we’re proud to announce more AI wins with Figma, GAP, Gordon Foods, Klarna, Macquarie Bank,Melexis, Mercedes, Signal Iduna, Valiuz, and Virgin Voyages. And we’re excited to be the official Cloud provider of the LA28 Games, where Google Cloud will bring our AI innovations to the Olympic and Paralympic Games.

AI that transforms how you work

Gemini Enterprise brings the best of Google AI to every employee through an intuitive chat interface that acts as a single front door for AI in the workplace. Behind that simple interface, Gemini Enterprise unifies six core components:

The platform is powered by Google’s most advanced Gemini models, creating the brains of the system, providing world-class intelligence for every task.

Through a no-code workbench, any user — from marketing to finance, and any other team — can analyze information and orchestrate agents to automate processes across the organization.

To deliver value from day one, it includes a taskforce of pre-built Google agents for specialized jobs like deep research and data insights, and you can easily augment this with custom agents your teams build or with solutions from our extensive partner ecosystem.

An agent is only as good as its context, so Gemini Enterprise securely connects to your company’s data wherever it lives — from Google Workspace and Microsoft 365 to business applications like Salesforce and SAP.

This is managed with a central governance framework, so you can visualize, secure, and audit all of your agents from one place.

And it is all built on a principle of openness with an ecosystem of over 100,000 partners. This ensures customer choice and fosters innovation.

By bringing all of these components together through a single interface, Gemini Enterprise transforms how teams work. It moves beyond simple tasks to automate entire workflows and drive smarter business outcomes — all on Google’s secure, enterprise-grade architecture.

Some companies offer AI models and toolkits, but they are handing you the pieces, not the platform. They leave your teams to stitch everything together. But you cannot piece together transformation.

That’s exactly what we built with Gemini Enterprise: a complete, AI-optimized platform — from our purpose-built Tensor Processing Units to our world-class Gemini models, all the way to the platform and agents that transform workflows. This is what it takes to deliver a truly unified AI fabric for your business, and it’s why customers are already putting Gemini Enterprise to work:

• Banco BV’s relationship managers used to spend hours doing their own analytics. Now, with the help of Gemini Enterprise, it’s done for them, leaving managers with more time to convert new business.
• Harvey is the leading domain-specific AI for legal and professional services, trusted by Fortune 500 legal teams. Powered by Gemini, lawyers are more efficient across contract analysis, due diligence, compliance, and litigation, saving hours and hours of time.

This isn’t just about making one task easier. It’s about making entire workflows smarter by searching and finding information from all your enterprise documents, applications, email and chat systems, and automating processes using agents with any of your enterprise applications.

Gemini Enterprise highlights our commitment to an open platform – working seamlessly in Microsoft 365 and Sharepoint environments. And when you use Gemini Enterprise with Google Workspace, you get further benefits. Today, we are announcing the first of many multi-modal agents harnessing the power of Gemini to understand and create text, image, video and speech, built right into the Workspace apps you already use:

• Video: With Google Vids, you can now transform one type of information, like a presentation, into a completely different format — an engaging video, complete with an AI-generated script and voiceover. The momentum for Vids has been incredible, with 2.5 million people using it every month.
• Voice: In Google Meet, we are bringing real-time speech translation to all business customers. This goes beyond just words, capturing your natural tone and expression to make conversations seamless, no matter what language you speak. This builds on the voice intelligence from our ‘take notes for me’ feature, which has seen usage grow more than 13x since the beginning of the year.

An agent is only as good as its context. Gemini Enterprise integrates with your organization’s data — wherever it lives — to build that context, and deliver relevant, accurate, and trustworthy results. Today, as part of Gemini Enterprise, we are announcing:

• A new Data Science Agent, in preview, to automate data wrangling and ingestion. It accelerates detailed data exploration, instantly finding patterns and streamlines complex model development by generating multi-step plans for training and inferencing, eliminating manual, iterative fine-tuning.

Customers like Morrisons, Vodafone, and Walmart are already using this agent to accelerate their data workflows and remove friction from the customer experience.

AI that transforms how you run your business

Customer engagement is one of the most critical use cases for AI adoption and our Customer Engagement Suite – our Conversational AI solution for web, mobile apps, call centers and point of sale – works alongside your customer service reps to answer questions via chat and voice and take actions. The business impact is real, and leading companies are seeing results now:

• Commerzbank was an early adopter of Customer Engagement Suite, using it to build Bene, its own specialized chatbot. They are now leveraging Gemini to further enhance the experience, enabling it to handle over two million chats and successfully resolve 70% of all inquiries.
• Mercari, Japan’s largest online marketplace, is overhauling its contact center with Google AI to foster an AI-driven customer service experience, which is projected to yield a 500% ROI by reducing customer service rep workloads by at least 20%.

Today, we are announcing true, next-generation conversational agents, in preview, that connect directly into Gemini Enterprise. These provide more value to you in the following ways:

1. How you build: We are introducing a new, easy-to-use low-code visual builder. You can build a customer engagement agent once, and configure it for all your channels — telephony, web, mobile, email, and chat. These new agents support over 40 languages.
2. The underlying intelligence: These next-gen agents are powered by our latest Gemini models. This means incredible, natural-sounding voices, with the ability to handle accent transitions and real-world noise from a bad phone connection with industry-leading accuracy and latency.
3. Your time-to-value: The new AI augmentation services and prebuilt specialized agents allow agents builders to build, test, deploy and monitor agents faster than ever. In addition, we also use AI assisted coaching to vastly increase the productivity of your employees. This makes your entire contact center — both human and digital — more efficient and effective.
4. Deep enterprise integration. These agents are designed to connect directly into Gemini Enterprise. This unlocks two key advantages: deeper personalization, using real-time context from all your business systems; and unified governance, allowing you to manage all your agents from the same central platform.

AI that transforms what you build

The ultimate transformation is when you use AI to create entirely new experiences for your customers. This starts with empowering the developers who are building your agents and applications. In just three months since launch, over one million developers are already building with Gemini CLI, an AI agent that lets developers interact with Google’s Gemini models directly from a terminal for task automation, code generation, and research using natural language. It has become an essential tool for developers around the world, whose workflows are becoming more complex every day. The best AI shouldn’t force you to switch contexts, it should adapt to your toolchain.

That’s why we introduced Gemini CLI extensions — a new framework to customize your command-line AI and connect it to the services you rely on most. This allows you to build a more intelligent, personalized workflow with a growing ecosystem of extensions from Google, and industry leaders like Atlassian, GitLab, MongoDB, Postman, Shopify, Stripe, and more. It turns your CLI from a simple tool into a personalized command center.

Innovation with agents is leading to an entirely new agent economy, where developers, ISVs and partners can build and earn revenue from specialized agents that communicate and transact with one another. To enable this, we have worked with the industry on an open standard called the Agent2Agent Protocol (A2A), which along with Model Context Protocol (MCP), sets the standard for how agents communicate.

But for agents to be truly autonomous, they must be able to transact. To provide a secure and auditable way for agents to complete payments, last month we announced a new, open protocol: the Agent Payments Protocol (AP2). This is a first-of-its-kind effort, developed with over 100 payment and technology partners, like American Express, Coinbase, Intuit, Mastercard, PayPal, ServiceNow, and Salesforce to establish how agents securely enable financial transactions.

By working with our partners and the larger community to build standardized protocols for key aspects, such as context, communication and commerce, we are laying the foundation for the agent economy.

Our customers are also building our Gemini models directly into their products:

• Klarna is using tools like Gemini and Veo to create bespoke lookbooks that are dynamic, personalized and impactful with shoppers, increasing orders by 50%.
• Mercedes-Benz builds cars with Google AI that can talk to their drivers. They are using Google Cloud’s Automotive AI Agent, which is built using Gemini on Vertex AI to power their MBUX Virtual Assistant, which enables natural conversations and provides personalized answers to drivers for things like navigation and points of interest.
• Swarovski creates personalized customer experience with Vertex AI resulting in a 17% increase in email open rates and 10x faster campaign localization.

This transformation goes beyond code. Our Gemini family of models have been used to create over 13 billion images and 230 million videos. For example:

• Figma is helping their community create more than ever. With tools across their platform powered by Gemini’s Flash 2.5 Image model (more commonly known as: Nano Banana), their users can now make high quality, brand-approved images with just a prompt, edit details with AI, and get all the variety their project needs.
• Virgin Voyages is using Veo’s “text-to-video” and Imagen to create thousands of hyper-personalized advertisements and emails. Each one perfectly matches Virgin Voyages unique brand voice at a scale that would be impossible just a year ago.

The number of customers using our AI models in Vertex continues to grow, including top brands, like: Adobe, Cathay Pacific, Kraft-Heinz, LATAM Airlines, Toyota, Unilever, and more.

The future of AI must be open

Google Cloud’s AI strategy is built on a foundational belief: The future of AI requires an open, collaborative partner ecosystem to ensure customer choice. To make this real, we have built a comprehensive agentic AI ecosystem with more than 100,000 partners supporting every layer of our AI stack – AI infrastructure, AI tooling, ISVs, and services partners. Today, we are advancing this ecosystem in four critical ways:

1. Expanded cross-platform workflows: We’re expanding our work with partners like Box, OpenText, ServiceNow, and Workday – tools you use everyday – to enable sophisticated, cross-platform workflows right out of the box.
2. Scaling with partners: Industry-leading partners, including BCG, Capgemini, HCLTech, Infosys, McKinsey, TCS, Wipro, and many others can assist with planning, deployment, and custom agent development to speed your adoption of Gemini Enterprise. And Accenture, Cognizant, Deloitte, KPMG, and PwC are making announcements today on their internal adoption and expanded services for Gemini Enterprise.
3. Discover validated agents: Customers can now use a new AI agent finder to discover the right agent for your needs, where you have assurance that the thousands of agents you can now find, filter, and deploy have been reviewed for security and interoperability.
4. Market & monetize agents: For those partners building AI agents, we provide you with a simple, powerful way to market and earn revenue from your solutions, instantly connecting you with millions of Google Cloud customers.

Enabling your transformation

Delivering this level of transformation requires a commitment to upskilling your teams. So today, we are announcing a comprehensive set of programs to help you succeed.

To upskill your entire workforce, we are introducing Google Skills, our new platform where training from across Google – from Gemini Enterprise to Google Deepmind – is available for free. On this platform, we’re announcing the Gemini Enterprise Agent Ready (GEAR) program, a new educational sprint designed to empower one million developers to build and deploy agents. Click here to be the first to use Google Skills and learn more about GEAR.

For organizations that want our experts embedded side-by-side with your teams, we are proud to announce a new team – Delta – an elite group of Google AI engineers to help you tackle your most complex challenges.

These programs are all designed to do one thing: help you and your teams build your future with AI.

Your foundation for the future

As AI transforms organizations around the world, Google is the only partner with the full set of offerings that you can tailor to your organization’s needs. And most importantly, we are delivering real business value to help you drive ROI from your AI investments.

This is the power of Gemini Enterprise: the new front door for AI in the workplace. We’re bringing the best of Google AI to every employee, for every workflow. And we’re excited to support you every step of the way.

From the classroom to the boardroom, the world of work is shifting at an incredible pace. As advancements in AI and cloud computing gather speed, it’s not just about adapting — it’s about discovering powerful new ways to thrive, regardless of your role.

To help everyone keep up, we’re announcing three major updates to our learning programs, timed with the launch today of Gemini Enterprise.

• A new platform, Google Skills, that will bring together nearly 3,000 courses and labs in one place — including content from across Google Cloud, Google DeepMind, Grow with Google and Google for Education.
• A new initiative, the Gemini Enterprise Agent Ready (GEAR) program, aims to empower one million developers to start building enterprise-ready AI agents with our new Gemini Enterprise platform.
• A partnership with the financial services company Jack Henry to help hire skilled individuals quickly as part of our skills-based hiring initiative.

With these updates, we’re delivering on our commitment to help everyone access the AI learning they need — including our Google Cloud customers in search of skilled developers.

What’s new for Google Cloud learners, customers and partners on Google Skills?

To support people at all skill levels — from students to developers to executives — we’re introducing Google Skills. This new learning platform is designed to help people develop the skills they need to be successful in today’s job landscape, and to enable businesses to find and develop the talent they need to thrive. In the last year alone, people have completed more than 26 million courses, labs and credentials — and now they’re all in one place.

In addition to content from across Google — like new AI research courses from Google DeepMind — this launch brings with it a host of new content for our Cloud customers to keep them on the cutting edge of AI skill building:

1. Gemini Code Assist: AI-powered learning and new skill badges

Gemini Code Assist will help engineers, developers, data scientists and more jump right into coding with Gemini without leaving the Google Skills platform. It’s been enabled in more than 20 hands-on labs and will be part of all relevant labs going forward. And developers can also prove Gemini Code Assist skills by earning a new skill badge: Kickstarting Application Development with Gemini Code Assist.

We’re also meeting the vibe-coding moment with two new skill badges for app devs: Building a Smart Cloud Application with Vibe Coding & MCP establishes foundational knowledge and practical skills in Model Context Protocol server development and vibe coding on Google Cloud. Deploy an Agent with Agent Development Kit empowers devs to build advanced AI systems where different AI parts work together smoothly, using common methods like the Model Context Protocol, Agent-to-Agent protocol and Agent Development Kit.

1. A better experience for Google Cloud customers and organizations

You asked. We listened. As part of Google Skills, we’ve kept the best of Google Cloud Skills Boost, while adding features you’ve been waiting for on the all-new Google Skills platform. For example, Cloud customers will continue to have access to the entire Google Cloud content library for free, now including new content from Google DeepMind.

We’ve also added a new feature that lets you assign the most relevant courses and hands-on labs to your teams. This personalization benefits your business and accelerates your team’s ability to innovate.

Plus, you can now use company leaderboards — customized for your organization — that spark friendly competition and add a dose of fun. And finally, for Google Skills admins, we’ll be adding features to make reporting more advanced. That means more data, more flexibility and more insights that let you keep track of your team’s progress in real time.

1. Cloud learning has never been more fun: new gamified features

For organizations, Google Skills makes it easier to keep your teams engaged and up to date. This is key: 74% of decision makers agree that technical learning resources improve employee productivity, and 71% of organizations realize revenue gains after engaging with these resources.¹ In other words, more learning is a universal boon to business.

But learning alone isn’t enough. It needs to be fun, engaging and easy to fit into your schedule. That’s why we’re bringing new AI-powered and gamification features to Google Skills to make learning more effective.

Gamified features:

• Leagues: Encourage friendly competition based on earned points with this dashboard widget.
• Achievements: Celebrate your learning milestones with new visuals and easy options for social sharing.
• Learning streaks: Promote consistent learning habits through bonus points and “streak freezes.”

GEAR: A new sprint to empower one million developers

Today, we’re also announcing the Gemini Enterprise Agent Ready (GEAR) program, a new educational sprint designed to empower one million developers on our new agentic platform, Gemini Enterprise. Through a cohort-based approach, we will help them build, deploy and manage agents, and as part of GEAR, developers can earn skill badges through Google Skills.

A direct path to employment; a faster way to hire

Building skills isn’t just good for individual careers — it’s also good for business. That’s why with Google Skills, we’re making it easier for people to get the skills employers are looking for, and for companies to find the talent they need to succeed.

Today, we’re announcing that for those who complete a Google Cloud Certificate in cybersecurity or data analytics in the U.S., there’s now a direct pathway to an interview with leading financial services firm Jack Henry. You’ll get to complete custom, hands-on labs that simulate the company’s real-world scenarios. These labs act as the first stage of the company’s hiring process, giving you a tangible way to showcase your skills and land a new job. We’re excited to expand the model to more Google Cloud customers in the future.

“We are excited for our collaboration with Google Cloud to reimagine talent acquisition. By leveraging Google Cloud Certificates, we have been able to more effectively identify and recruit top talent, helping to fuel our growth to fill critical skill gaps.” – Holly Novak, Chief People Officer, Jack Henry

This initiative is especially important because businesses are actively looking for talent. A recent study found that 82% prefer to recruit and hire professionals who hold these credentials.²

For Google Cloud customers interested in bringing on skilled individuals to your company, learn more about the program here.

We’re just getting started. Whether you’re an individual looking to get hired or a business leader aiming to upskill your teams, there’s something for everyone to thrive in this new world of AI.

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¹ Google/Ipsos, Cloud Learning Services Market Pulse, Quantitative Portion Fielded Sept-Oct 2024, Qualitative Portion Fielded Oct-Nov 2024, (U.S., U.K., FR, DE, IN, BR, MX, JP, AU/N.Z.)

² Google/Ipsos, Cloud Learning Services Market Pulse, Quantitative Portion Fielded Sept-Oct 2024, Qualitative Portion Fielded Oct-Nov 2024, (U.S., U.K., FR, DE, IN, BR, MX, JP, AU/N.Z.)

Google Cloud believes the future of AI should be open, flexible, and interoperable. Today, with the launch of Gemini Enterprise – our new agentic platform that brings the best of Google AI to every employee, for every workflow – we’re introducing powerful new opportunities for partners to integrate their solutions and bring them to market.

Our AI ecosystem is already thriving, with thousands of partner-built agents available to Google Cloud customers today. More importantly, this curated set of agents has been validated by Google Cloud, ensuring customers have confidence in their quality and security as they use agents to transform their businesses.

Extending partner-built agents in Gemini Enterprise

Our goal is to make Gemini Enterprise the central destination for customers to access the agents they use daily, including those from leading technology and SaaS providers. With the combination of Gemini Enterprise and the Agent2Agent (A2A) protocol, agents can securely communicate and coordinate complex tasks with each other. Some of the partners announcing Gemini Enterprise-compatible agents today include:

• Box: The Box AI agent lets users ask questions, summarize complex documents, extract data from files, and generate new content while respecting existing permissions in Box.
• Dun & Bradstreet: D&B’s Look Up agent uses the D-U-N-S Number, a globally trusted identifier, to unify business data from internal and third-party sources for accurate and efficient integration across enterprise workflows.
• Manhattan Associates: Manhattan’s Solution Navigator agent provides instant answers on Manhattan Active solutions, policies, and operations to accelerate response times and efficiency.
• OpenText: Core Content Aviator simplifies content management, enabling users to search and summarize information with AI assistance, including document generation and multilingual translation.
• Salesforce: Agents built on Agentforce and data from Slack will be accessible to users within Gemini Enterprise, enhancing their AI-powered productivity and business insights.
• S&P Global: S&P’s Data Retrieval agent helps users analyze earnings calls, perform market research, and retrieve financial metrics–all with direct source citations.
• ServiceNow: Enabled by A2A and ServiceNow AI Agent Fabric, ServiceNow AI Agents for Service Observability connects with Google Gemini-powered agents to detect, investigate, and recommend fixes for issues in customer cloud deployments – streamlining incident management, and enabling greater organizational agility.
• Workday: Workday agents, such as its Self-Service Agent, deliver immediate insights and enable quick actions, like flagging potential budget overruns, submitting time off, creating HR cases, managing pay information, and more – all directly within the employee’s flow of work.

These and many other partners have committed to integrate their agents with Gemini Enterprise, including Amplitude, Avalara, CARTO, Cotality, Dynatrace, Elastic, Fullstory, HubSpot, Invideo, Optimizely, Orion by Gravity, Pegasystems, Quantum Metric, Supermetrics, Trase Systems, UiPath, and Vianai.

Discover validated agents using natural language search

In addition to deploying partner agents that integrate with Gemini Enterprise, customers can also now use a new, Gemini-powered AI agent finder – with natural language search – to help discover the right AI agents for their needs. Customers can search for agents from trusted vendors and filter by industry, use case, and whether they have been validated for A2A and deployment to Gemini Enterprise. These agents can then be purchased from Google Cloud Marketplace or directly through partners, and deployed into their environments.

This curated discovery experience is enabled by our enhanced AI agent ecosystem program and a rigorous framework for partners to validate their agents. We’ve also introduced the new “Google Cloud Ready – Gemini Enterprise” designation to recognize agents that meet our highest standards for performance and quality, helping accelerate adoption of trusted solutions and giving partners a new path to monetize their agents.

Growing partner services to help customers succeed with AI

Google Cloud remains partner-led in our professional services approach. With the launch of Gemini Enterprise today, our consulting partners are already expanding their services offerings to help customers accelerate their adoption of AI agents. In fact, many of these partners are already powering their own businesses with Gemini Enterprise. Major expansions include:

• Accenture is driving successful adoption of Google Cloud’s AI technology with clients across industries; expanding agentic capabilities via the Accenture and Google Cloud generative AI Center of Excellence; and launching agents on Google Cloud Marketplace.
• Deloitte is leveraging its “Agent Fleet” of live agents to help clients utilize Gemini Enterprise to deploy industry-tailored agents and co-innovate at scale.
• Capgemini has developed a variety of agents with Google Cloud’s AI technology across sectors, which it will bring to Gemini Enterprise and the Google Cloud Marketplace.
• Cognizant is accelerating agentic AI adoption for its clients and through internal use of Gemini Enterprise and by investing in Google Cloud Centers of Excellence around the globe.
• GlobalLogic, a Hitachi Group Company, will adopt Gemini Enterprise internally and provide digital engineering services to accelerate customer adoption, including building AI Agents securely and at scale.
• KPMG is using Gemini Enterprise to enhance the speed, accuracy, and quality of client delivery and to elevate the employee experience at KPMG with AI and agents, making everyday work easier.
• PwC is advancing client AI transformation by combining its agent OS technology with Gemini Enterprise, including the deployment of agents it has used successfully internally.

Get started bringing agents to Gemini Enterprise

Gemini Enterprise is available today and includes access to thousands of agents from our ecosystem. Partners interested in learning more can visit the AI Agent Program page.

We’re committed to providing partners with the platform and resources needed to scale their AI agents on Gemini Enterprise, and we look forward to seeing the solutions they deliver to customers.

Startups are using agentic AI to automate complex workflows, create novel user experiences, and solve business problems that were once considered technically impossible. Still, charting the optimal path forward — especially with the integration of AI agents — often presents significant technical complexity

To help startups navigate this new landscape, we’re launching our Startup technical guide: AI agents. It provides a systematic, operations-driven roadmap for embracing the potential of agentic systems.

What does this potential look like? AI agents combine the intelligence of advanced AI models with access to tools so they can take actions on your behalf, under your control. Unlike traditional AI, agentic AI can break down intricate tasks, refine plans, and dynamically utilize external resources and tools. The key takeaway is that AI agents can tackle complex, multi-step problems, ultimately transforming from a passive tool into a proactive problem-solver.

If your startup is looking to get in on the agentic AI action, here are some initial steps to consider. And when you’re ready to get building, you can get more details in our guide or even reach out to one of our AI experts at Google Cloud.

Choose your path: Build, use, or integrate

Every startup’s journey is unique, which is why Google Cloud offers a flexible agent ecosystem that supports the comprehensive development of agentic systems. You can:

• Build your own agents: For teams that require a high degree of control over agent behavior, the open-source Agent Development Kit (ADK) is your go-to development framework. ADK is built for a custom, code-first approach, empowering developers to build, manage, evaluate, and deploy AI-powered agents. For an application-first approach, Google Agentspace orchestrates your entire AI workforce and empowers non-technical team members to build custom agents using a no-code designer.
• Use Google Cloud agents: With rapid prototyping and easy ways to integrate AI into your existing apps, managed agents let you focus on core business logic rather than managing infrastructure. Gemini Code Assist is an AI-powered assistant for developers, while Gemini Cloud Assist is an AI expert for your Google Cloud environment.
• Bring in partner agents: For more specialized use cases, you can easily integrate third-party or open-source agents into your stack via the Google Cloud Marketplace. You can also explore the Agent Garden to deploy prebuilt ADK agents that already support data reasoning and inter-agent collaboration.

No matter which path you choose, our ecosystem is designed for interoperability, built on open standards like the Model Context Protocol (MCP) and the Agent2Agent (A2A) protocol.

4 steps for building your first agent

The Startups technical guide: AI agents provides a complete roadmap for building production-ready AI agents. Here’s four core steps we’ve identified that can help define your first agent, using Agent Development Kit (ADK).

Step 1: Give your agent an identity

First, define your agent’s core identity. You’ll want to give it a unique name for logging and delegation, a clear description of its capabilities so other agents can route tasks to it, and identify the right AI foundation model (like Gemini 2.5 Pro or Gemma) to power its reasoning. Precision here is critical. The model you’re using treats every part of this definition as a prompt, and vague descriptions can lead to “context poisoning,” causing the agent to pursue incorrect goals.

Step 2: Write the “prime directive” with instructions

Next, give your agent its “prime directive” using the instruction parameter. This is where you define its persona, core objectives, and do’s and don’ts. Effective instructions clearly specify the desired outcomes for your agent, provide examples for complex tasks (e.g. few-shot prompting), and guide the agent on how to use its tools.

Step 3: Grant superpowers with tools

Transform your agent from a pure conversationalist into a system that can take action by equipping it with functions to call external APIs, search databases, or interact with other systems. In doing so, you grant it broader capabilities. For example, a bug assistant agent uses tools to fetch user details from a CRM or create a ticket in a project management system. Since the agent chooses which tool to use based on its name and description, making them clear and unique is crucial to avoid looping behaviors or incorrect actions.

Step 4: Master the lifecycle: test, deploy, operate

Building an agent is a continuous cycle, not a one-off task. Because agentic systems are non-deterministic, standard unit tests are insufficient. Our guide shows you how to evaluate an agent’s “trajectory” — its step-by-step reasoning — to ensure quality and reliability. This operational rigor, which we call AgentOps, is key to confidently deploying your agent on platforms like Vertex AI Agent Engine or Cloud Run and operating it safely in production.

Agents already in action

Startups are constantly innovating their agentic journeys , here’s a look at two startups that use Google Cloud’s models and architecture to run their agentic systems:

Actionable insights for better employee engagement

Wotter, a provider of next-generation Employee Engagement solutions, seeks to better understand what employees want and empower organizations with the insights they need to get the best out of their people by asking the right question to the right person at the right time.

Gemini 2.5 Flash was the right foundation model for Wotter’s smart assistant, blending speed with long-context reasoning. Wotter’s Flash models use agentic methods to manage extensive and ongoing sources of data, such as employee interactions and feedback, while still responding to queries on this data in seconds – and at a lower cost per query.

Eliminate a long-standing legal industry pain point

As people in the legal industry know too well, complex document reviews can ruin nights and weekends while turning focus away from strategic work. Enter Harvey, which is equipping legal professionals with domain-specific AI to maximize efficiency and keep legal professionals’ attention on activities that move the needle for their firms and clients.

Harvey evaluated several foundation models and ultimately found that Gemini 2.5 Pro achieved the leading score of 85.02% on its BigLaw Bench benchmark, the first of its kind to represent complex legal tasks. Gemini 2.5 Pro showcased strong reasoning across inputs consisting of hundreds of pages of materials—a common scenario in legal work. The model then used these materials to generate longer-form and comprehensive outputs, enabling deeper insights and analyses.

These core capabilities proved Gemini 2.5 Pro’s potential across complex legal work that requires reasoning over large sets of documents to support diligence, review, and use case drafting. Further, Vertex AI provides the stringent security and privacy guarantees that build trust in the Harvey platform among clientele. Gemini and Vertex AI are now an important part of Harvey’s vision for future product development.

Build what’s next, faster

The Startup technical guide: AI agents provides the blueprint your team needs to turn your vision into a production-ready reality. By using a code-first framework like ADK and the operational principles in this guide, you can move beyond informal “vibe-testing” to a rigorous, reliable process for building and managing your agent’s entire lifecycle. For your startup, this disciplined approach becomes a powerful competitive advantage.

No matter where you are with AI adoption, we are here to help. Contact our Startup team today and you could get up to $350,000 USD in cloud credits with the Google for Startups Cloud Program,

We recently hosted our first-ever AI Builders Forum, where we gathered with hundreds of the top founders, VCs, advisors, researchers, and teams powering the startups who are building the future with AI. And now, this week, many of us are together again in San Francisco for Tech Week.

A big reason for us to gather with our peers and the next generation of groundbreaking companies is that at Google Cloud, we’ve always worked to provide companies with the very same tools and infrastructure that power Google’s own services and drive our continued growth. In recent years, we have been able to take that to an entirely new level, making our leading generative AI technology available to even the youngest startups.

During the AI Builders Forum, we showcased the work of dozens of startups who have taken that technology in new and exciting directions. There’s so many more hard at work with Google Cloud that we wanted to highlight as many as we could. Here, we’ve gathered 150 to be exact, breaking them out by the sectors and specialties in which they’re creating exciting new offerings that are changing the way we work, create, collaborate, and cure.

For those looking to join their ranks, we encourage you to join our Google for Startups Cloud program, with access to valuable credits and advice from Google experts and experienced VCs. And when it comes to the especially hot segment of AI agents, we’ve just introduced our Startup Technical Guide: AI Agents. It’s an in-depth collection of best practices and step-by-step guidance for building and scaling agentic AI.

We hope this list serves as inspiration for your own work — and that you’ll find yourself being recognized soon enough, too. All it takes is the right AI, the right partners, a good team, and a great idea.

• Arize AI, an AI agent and engineering platform, partners with Google Cloud to help organizations successfully develop, evaluate, and observe their generative AI applications. The Arize AX platform seamlessly integrates with Vertex AI models and runs on Google Kubernetes Engine (GKE), which allows a very lean operations team to easily scale services and provide deep visibility into every layer of AI systems.
• Augment Code, an AI coding assistant, integrated Anthropic’s Claude 3.5 Sonnet via Vertex AI to power its codebase chat feature. This delivered an instant improvement to chat performance after quick implementation, enhancing security and allowing customers to build and troubleshoot code faster.
• Aviator, an engineering productivity platform, uses Google Kubernetes Engine, Vertex AI, and Gemini to scale its engineering productivity platform to thousands of users while accelerating the development of new generative AI features.
• Cursor is an AI-powered code editor that integrates advanced AI features like autonomous agents and codebase-aware chat. It aims to create a highly effective human-AI programmer by automating tasks, understanding entire codebases, and accelerating development velocity, using models like Gemini and Anthropic’s Claude on Google Cloud’s Vertex AI.

• DeepSource, a platform for code quality and security, leverages Gemini and Google Kubernetes Engine (GKE) to help developers automatically analyze and remediate code. The platform uses Gemini-powered AI agents for its Autofix™ remediation engine, which increases the accuracy of its static analysis and provides automated fixes. Running on GKE, DeepSource can automatically scale to process tens of millions of lines of code per day, reducing operational costs and accelerating time to market for over 6,000 companies.
• Factory AI, a platform for agent-driven software development, accelerates engineering by unifying context from sources like GitHub and Jira to delegate tasks like feature development and migrations. It uses Gemini 2.5 Flash for data ingestion and Gemini 2.5 Pro for advanced code/document generation.
• Fireworks AI, a generative AI platform, uses Google Kubernetes Engine and Compute Engine to run its fast and efficient inference engine. This enables the company to process over 140 billion tokens daily, offering customers high uptime and throughput with lower latency and costs.
• Lovable, an AI software engineer, leverages Google Cloud’s Vertex AI to deploy and unify its core language models, including Gemini and Anthropic’s models. This unique orchestration enables users to create complete, full-stack web applications from plain English descriptions, effectively cutting the time required for prototype development from weeks to minutes and app development from months to hours.
• Naologic, an AI application platform, uses Gemini APIs, Google Kubernetes Engine , and MongoDB Atlas on Google Cloud to build apps on top of legacy ERPs. The solution delivers fast query responses regardless of complexity, enabling powerful, natural-language chat and scaling for complex AI workloads like RAG and image search.
• Qodo addresses critical code quality concerns with an agentic platform that works within existing developer workflows. Qodo integrates into Vertex AI Model Garden and provides automated pull request reviews at no cost to open-source projects.
• Resolve AI, an always-on AI SRE, autonomously investigates incidents and helps run production systems using code, infrastructure, and observability data. With the intelligence and performance of Gemini on Vertex AI, Resolve AI improves MTTR, reliability, and engineering velocity for its customers.
• Sieve, an AI research lab focused on video data, builds multimodal AI systems to automate dataset creation, improve data quality, and provide relevant metadata that powers frontier model training. Sieve uses Vertex AI for large-scale video processing, content moderation, and indexing, including tasks like text recognition, captioning, and enrichment.
• Systalyze, an enterprise AI deployment platform, reduces the cost and complexity of AI. Through a partnership with Google Cloud, it reduces deployment costs by up to 90% and accelerates fine-tuning, inference, and agentic AI by 2–15x, while keeping data fully private and secure.
• Turbopuffer, a startup offering serverless vector and full-text search, uses Google Cloud Storage, Google Kubernetes Engine, and Google Compute Engine to help AI businesses overcome the high costs and complexity of traditional database architectures. ​Its solution has reduced AI database cost by up to 90% for customers, manages over 1 trillion documents, and handles more than 10 million writes and 10,000 queries every second.
• Vercel democratizes access to AI models through its AI SDK and AI Gateway, making it seamless for developers to integrate agentic capabilities into their applications. By providing unified access to leading models like Google’s Gemini through a single interface, Vercel has enabled teams to build AI-powered features faster and more reliably.
• VESSL AI, an MLOps platform, uses Google Cloud to accelerate AI model development and reduce costs for its users. By leveraging Google Kubernetes Engine, VESSL AI can dynamically scale ML workloads, helping users create AI models up to four times faster and realize up to 80% savings on cloud expenditures. The platform’s integration with Vertex AI provides users with access to powerful models and AutoML solutions, further streamlining the MLOps lifecycle.
• Windsurf provides an AI-powered code completion and generation tool for developers. Their AI integrates directly into IDEs, offering suggestions, generating code, and refactoring existing code. Windsurf uses Gemini 2.5 Pro to power its coding assistance IDE, and to support integrations with Cognition’s Devin AI.

• Atropos Health, a healthcare data analytics company, optimized its GENEVA OS to work with Google Cloud’s Healthcare Data Engine (HDE) and BigQuery. This enables customers to efficiently and securely convert data into valuable insights and evidence.
• Cerebra AI develops AI software for analyzing non-contrast CT (NCCT) scans, with a focus on early stroke and cancer detection. It fine-tunes MedGemma on NCCT images and leverages Gemini’s few-shot generalization capabilities to rapidly adapt the model for various diagnostic tasks.
• CitiusTech, a global Healthcare technology services firm, uses Google Cloud to improve patient experience, reduce administrative burden on clinical staff, and save costs for healthcare systems. The company has developed an AI search solution using Vertex AI to efficiently connect patients with the right specialists and automate critical workflows.
• Congruence Therapeutics, a computationally driven biotechnology company, uses its proprietary platform, Revenir, to build a pipeline of small molecule correctors. The platform identifies novel allosteric and cryptic pockets in proteins to rescue aberrant function.
• CoVet is an AI assistant built by veterinary professionals, for veterinary professionals, that uses Gemini, Cloud Functions, and other GCP solutions to help veterinary teams automate administrative work, save hours every day, and refocus on what matters most: exceptional patient care.
• Digital Diagnostics, a healthcare diagnostics company, uses Google Cloud’s secure infrastructure to enhance the reach of LumineticsCore, its AI-powered diagnostic tool for diabetic retinopathy. This approach protects sensitive health data and ensures patient privacy and regulatory compliance.
• DNAstack, a leading genomics data management and analysis platform, leverages Google Cloud’s scalable infrastructure and advanced analytics tools to accelerate research and discovery in personalized medicine.
• Evogene uses Google Cloud and Vertex AI to replace life sciences’ costly “spray and pray” molecular discovery — testing millions of molecules hoping to stumble into effective ones — with their computational platform. They now process 40 billion molecules versus previous millions, while using Vertex AI to develop a cutting-edge small-molecule foundation model that dramatically accelerates drug discovery timelines.
• GenBio AI, a computational biology company, uses Google Cloud to power six specialized AI models in developing AI-driven digital organism simulators. These models simulate biological programming to address critical challenges in medicine and biology.
• Immunai tackles drug development’s decade-long timeline with AMICA, the world’s largest immune-focused single-cell database containing hundreds of millions of cells. Using Google Cloud GPU clusters, they train models that transform complex immune mechanisms into actionable recommendations for 30+ biopharmaceutical partners.
• Infinitus, the first trusted agentic healthcare communications platform, automates clinical and administrative conversations at scale. Our AI agents powered by Gemini’s multimodal capabilities have completed over 5x more conversations than any other solution with payors, patients, and providers to drive revenue and improve health outcomes
• iSono Health, a medical imaging company, developed a Virtual Sonographer, an intelligent, automated 3D Ultrasound platform powered by Google Cloud AI. The platform brings breast imaging directly to the point of care, providing fast, accessible, and repeatable imaging.
• Menten AI, a biotechnology company, uses Google Cloud’s high-performance compute and machine learning capabilities to accelerate the development of peptide therapeutics. This allows the company to rapidly design and optimize novel drug candidates.
• Moonwalk Bio, a preclinical-stage biotechnology company, leverages epigenetic biology and AI to pioneer new medicines for obesity and cardiometabolic disease. Their platform determines the causal relationships between genes and disease pathways for therapeutic targeting.
• Pear Health Labs, a health & fitness AI platform, develops personalized interventions to prevent chronic conditions. It powers recommendations, content search, & dynamic audio coaching. It uses Vertex AI Voice Generation, Vector Search in BigQuery, & the engineering team leverages Gemini Code Assist.
• Sami, a tech-enabled health insurance company in Brazil, built its entire infrastructure on Google Cloud from day one. The company uses AI tools such as Gemini, Notebook LM, and Vertex AI to transform healthcare delivery and accelerate critical processes like prescription validation to seconds. Sami enables information flow across its partners, delivering high-quality, accessible healthcare at scale.
• SandboxAQ is expanding its usage of Google Cloud and running a new AI drug discovery simulation platform on Google Cloud.
• Sully.ai, a healthcare AI company, has built an app store for AI agents designed specifically for healthcare professionals. The platform provides support to clinicians on administrative tasks, so they can focus on patients.
• Tali.ai is the leading medical AI scribe platform, designed to reduce the administrative burden of clinicians. Integrated with multiple EMRs across the U.S. and Canada, it leverages Google’s Vertex and Gemini models to automate clinical note-taking during patient encounters and extract key insights.
• Think Research, a provider of knowledge-based digital health software solutions, uses Google Cloud’s scalable infrastructure and analytics tools to power its platform. This enables the company to deliver more efficient patient care and improve health outcomes.
• Ubie, a healthcare-focused startup founded in Japan, is using Gemini models via Google Cloud to power its physician assistance tool.
• Ufonia helps physicians deliver care Ufonia, a clinical AI company, helps physicians deliver care by using AI to automate clinical consultations with patients. Google Cloud’s full AI stack, including infrastructure, models on Vertex AI Model Garden, BigQuery, and Google Kubernetes Engine, powers its platform by using AI to automate clinical consultations with patients. It is using Google Cloud’s full AI stack to power its platform, including infrastructure, models on Vertex AI Model Garden, BigQuery, and GKE.
• Via Scientific, a bioinformatics company, partners with Google Cloud to deliver Via Foundry, an enterprise-grade platform that uses Gemini and Vertex AI to make the drug discovery process more efficient. The platform transforms complex biological data into actionable insights that can accelerate discoveries.
• Virgo Surgical, a medical video solutions provider, uses Google Cloud Storage and Google Kubernetes Engine to host and process over 1.75 petabytes of video data. This data has been used to create EndoDINO, an AI foundation model for endoscopy that achieves high performance in medical imaging applications.

• Gobii provides AI Agents that automate complex web tasks like forms and workflows directly in the browser. To power these intelligent agents, Gobii leverages Google Cloud, utilizing Vertex AI and our scalable GKE infrastructure.
• Hebbia, a legal and financial research company, integrated Gemini models into its Matrix platform to help organizations build AI agents capable of working across all of their data.
• LiveX, customer service AI agents, uses Google Kubernetes Engine Autopilot and NVIDIA GPUs to power its platform. These technologies reduced total cost of ownership by 50% and operational costs by 66% while supporting an 85% reduction in customer support costs for one of its clients.
• Parallel is using Gemini models to power new products including an API for AI agents to perform high-value tasks using web data.
• Qualia Clear is an agentic system that transforms real estate closings by automating manual title & escrow workflows. It uses tool calling, Gemini 2.5 Flash & Pro, and Google Agent Development Kit to process emails and documents and simplify reporting, improving efficiency and customer service.
• Replicant automates customer conversations for enterprise brands using voice and chat AI agents that replicate the expertise of your very best agents. Gemini helps Replicant deliver consistent service 24/7 that deploys quickly, scales effortlessly and continuously improves to boost ROI and CX.
• Skyvern helps companies automate browser-based workflows with AI. Skyvern uses Large Language Models (LLMs) like Gemini 2.5 Pro and computer vision, to interact with websites, enabling it to automate tasks like filling out forms, procuring materials, and downloading invoices. Skyvern’s AI agents can adapt to website changes, making automation more robust.
• Torq uses agentic AI to automate the entire security operations lifecycle through Socrates, an AI SOC analyst that coordinates specialized agents. Running on Google Cloud’s infrastructure, teams achieve 90% automation of tier-1 analyst tasks auto-remediated without human involvement, 95% decrease in manual tasks and10x faster response times.

• Altumatim, a legal tech startup, uses a platform powered by Gemini on Vertex AI to analyze millions of documents for eDiscovery. This accelerates the process from months to hours, improves accuracy to over 90%, and enables attorneys to focus on building compelling legal arguments.
• Anara, a generative AI research assistant, helps users find and understand scientific documents with verifiable AI summaries and insights. It uses Google Cloud’s scalable infrastructure, AI Studio, and Cloud Functions to power its models and data processing for a global user base.
• Clavata.ai delivers an integrated AI governance and safety platform with intelligent, multi-modal, real-time evaluation engine powered by Gemini. Our tools enable proactive policy enforcement, dynamic debugging, iteration, observability, and problem prevention.
• Harvey, a legal AI company, uses Gemini 2.5 Pro on Vertex AI to automate complex document reviews, a major pain point in the legal industry. The platform provides domain-specific AI that can reason over hundreds of pages of materials, enabling legal professionals to maximize efficiency and focus on strategic work.
• Inspira, a legal tech company, tackles the time-intensive challenge of legal document analysis by providing lawyers with an AI-powered solution built on Google Cloud. Leveraging Gemini, Vertex AI, and BigQuery, Inspira’s platform automates legal document search, analysis, and drafting to reduce workflow times by 80%, allowing lawyers to find answers and relevant decisions in minutes or hours instead of weeks.
• Instalily uses Google Cloud with Gemini 2.5 and Vertex AI to power InstaWorkers™ that transform sales, service, and operations. At a leading field service provider, InstaWorkers™ cut the technician’s diagnosis time from 15 minutes to under 10 seconds, lowered serving costs by 98 percent, and drove a 99 percent improvement in end-to-end workflow speed.
• Markups.ai, an AI contract negotiation agent, turns a days-long human legal review into a minute(s) automated process. By simply emailing a contract, clients receive customized revisions and analysis almost instantly. Gemini 2.5 Pro enabled us to go from handling only first revisions of NDAs, to any revision of any contract (MSAs, DPAs, etc.).
• monday.com, a work management platform trusted by more than 245,000 customers worldwide, leverages Veo to produce training videos, social content, and internal communications in a fraction of the time — empowering all employees, not just designers, to move faster and focus on impact.
• NoBroker, a real estate platform, uses its ConvoZen AI, powered by Gemini and L4 GPUs, to automate customer support across multiple Indian languages. The platform processes 10,000 hours of recordings daily, with AI agents projected to handle 25-40% of future calls and save customers $1 billion annually.
• ObraJobs, a job platform, connects candidates with relevant opportunities, streamline the hiring process, and deliver personalized recommendations for both job seekers and employers. Obra uses Vertex AI to power candidate matching and personalized job recommendations, supported by Cloud Storage, Cloud Run, Cloud Scheduler, Cloud Tasks, and Firestore.
• Provenbase has built its talent recruitment tool for businesses on Google Cloud and is now powering its transformative Deep Search for talent feature using Google Cloud AI.
• Story, an intellectual property startup that powers licensing and monetization services, is working with Google Cloud’s web3 services and infrastructure to bring new capabilities to developers on its platform.
• Upwork, the world’s human and AI-powered work marketplace, connects businesses with independent professionals. By leveraging GCP’s Vertex AI Text to Speech API, Upwork delivers faster, more accurate talent matching and hiring efficiency for clients and freelancers.
• Wotter, an employee engagement platform, uses a Gemini-powered smart assistant and Google Cloud’s robust AI capability to provide real-time insights into employee sentiment. It accurately predicts flight risks and offers actionable “Wott-if” scenarios, enabling leaders to build a data-driven people strategy.

• Bynry‘s SMART360 leverages Google Cloud’s robust infrastructure to empower small and mid-sized utilities to enhance operational efficiency and customer satisfaction.
• Kraftblock, a green tech company, uses Google Cloud Compute Engine to run simulations for its high-temperature thermal energy storage systems, helping energy-intensive industries like steel and ceramics decarbonize. This support helps the green tech startup optimize its solution and scale faster.
• Labellerr, a data labeling engine, uses Vertex AI and Cloud Run to automate annotation and smart QA to help ML teams process millions of images and thousands of hours of videos in just a few weeks.
• Physical Intelligence recently partnered with Google Cloud to support model development, using our secure and scalable AI infrastructure.
• tulanā, an intelligent decision support provider, has a highly customizable platform that uses forecasting, optimization, simulation, and AI to help enterprise clients make better decisions across supply chains and physical infrastructure. tulanā is using Cloud Run to horizontally scale its optimization workloads, Gemini for intelligent ETL processes, and Cloud SQL and Big Query to store customer data.

• Albo, a Mexican neobank, uses Gemini models to power its “Albot” AI chatbot that provides 24/7 financial advice, customer onboarding, and support to millions of first-time banking users. The platform advances financial inclusion while streamlining regulatory compliance and improving operational efficiency.
• Bud Financial, a data intelligence provider focused on banking clients, leverages DataStax Astra DB on Google Cloud with Gemini. The platform enables ultra-fast processing of complex financial data, helping clients reduce fraud by over 90% and shortening the time required to access critical data analytics from weeks to minutes.
• Causal, a financial planning platform, uses Cloud SQL and Gemini models to power its data foundation and accelerate innovation. By offloading database management, the company built an AI-powered wizard that helps users connect data, analyze patterns, and generate financial models in just five minutes.
• CERC, a financial infrastructure company, manages more than 500 million daily transactions using Databricks, BigQuery, and Gemini. This increased processing capacity by 10x without adding to the workforce, allowing the company to process millions in revenue forecasts in just two minutes and accelerate analytics for customers.
• DataCurve, a frontier coding data analytics provider, addresses complex data challenges by combining Web3 and generative AI on Google Cloud. Its platform uses AI agents for deep data analysis and Web3 for data authenticity, delivering insights that help customers take action and improve engagement.
• eToro, a global trading and investing platform, has pioneered a groundbreaking approach to marketing by using Veo to create advertising campaigns. This enables eToro to rapidly generate professional-quality, culturally specific video content across the global markets it serves, which would traditionally require extensive production timelines and significant budgets.
• Fiscal.ai is reinventing financial data infrastructure. Its AI-native platform transforms unstructured public filings into clean, standardized data in minutes, replacing the slow, error-prone legacy of manual aggregation and delivering the mission-critical insights that today’s top investors demand.
• Rogo, a generative AI platform built for the financial industry, uses Google Cloud solutions like Dataflow, Spanner, and Vertex AI to automate complex research and analysis for the world’s leading investment banks and private equity firms. Gemini 2.5 Flash enabled the platform to cut AI modeling time from months to hours and reduce hallucination rates from 34.1% to 3.9%.
• Stax AI, a retirement administration platform, uses Google Cloud’s generative AI and MongoDB to automate data extraction from complex financial documents. The solution processes thousands of brokerage statements in minutes, not hours, helping administrators respond to client inquiries and meet compliance deadlines in a fraction of the time.
• Stream, offers financial tools to employers and employees and is using Gemini models to handle more than 80% of its internal customer inquiries, including questions about pay dates, balances, and more.
• WealthAPI, a German fintech company, uses DataStax Astra DB on Google Cloud with Gemini to deliver real-time financial insights to millions of users. The platform’s scalability allows it to analyze hundreds of thousands of transactions per second and has reduced response times by 90% for its customers.

• Afooga, an AI-powered content experimentation factory, enables businesses to generate, test, and distribute content at massive scale from a single hypothesis, automatically optimizing across TikTok, Meta, YouTube, and more. Afooga leverages Vertex AI and Veo for generative video capabilities, and is architected entirely on Google Cloud.
• Alson AI, a creative platform provider, uses Veo and Gemini to power its creativity platform that helps creators turn ideas into illustrated books and animations, reducing production time from months to minutes and costs from thousands of dollars to $25.
• Cartwheel, a generative animation platform, helps users tell stories faster and more creatively. Its tool uses Gemini Flash for character creation prompts, Imagen for reference-image creation for 3D character development, and Veo 3 for video-to-animation input control that makes output editable by artists.
• ComfyUI, an open-source engine for visual AI, helps creators prototype and automate media generation with pre-set models and more than 20,000 extensions. The platform integrates Gemini 2.5 and Veo 3 for multimodal creation and runs on Google Cloud infrastructure.
• Connected-Stories, an AI creative platform, uses Gemini and Imagen on Vertex AI to help brands overcome manual content personalization challenges. The platform’s AI creative assistant analyzes briefs and turns them into sophisticated strategies, enabling brands to create personalized content at scale and optimize campaigns in real-time.
• fal, a generative media platform for developers, accelerates generative AI model inference to improve the speed with which content is generated. The fal team is working with Google Cloud to leverage its Veo 2 technology to help its users create videos with realistic motion and high-quality output.
• HeyGen, an AI-powered video generation platform, makes creating, translating, and personalizing high-quality videos simple and accessible. HeyGen’s core product leverages Gemini 2.5 Pro, Flash, and Flash-Lite to streamline content creation. With one prompt, HeyGen automates video planning, intelligently analyzes user-generated footage, and optimizes content through advanced visual and audio processing.
• Higgsfield.ai, a generative AI video startup, uses its foundational model on Google Cloud and Vertex AI to enable video creation, helping smaller companies create realistic videos faster and more cost-effectively compared to traditional methods.
• Krea.ai, a creative suite of AI tools, offers real-time image/video generation and personalized model training for artists and marketers. It integrates with Google Cloud, including models as Veo3 and Nano Banana, to provide access to advanced models, enabling users to create high-quality ads, product photos, and game assets.
• Mosaic lets you build and run multimodal video-editing AI agents. A canvas of creative tools becomes your building blocks, enabling simultaneous edits and many versions on autopilot—powered by Gemini 2.5 Pro’s video understanding and Google Cloud (Storage + Cloud Run) for scalable pipelines.
• Nim.video is an AI-first platform for instant short-form video generation from a single prompt. The multimodal platform uses top generative models, including Veo3 and Veo3 Fast, for text-to-video synthesis. It runs on Vertex AI, enabling scaled experiments and orchestration of services like speech recognition and TTS.
• OpenArt empowers social media creators and SMBs to turn ideas into stunning videos in minutes – complete with motion, music, and a narrative arc in one click. Powered by Gemini image models and Google’s Veo3 video model, it makes creating viral posts and brand content fast and effortless.
• Photoroom, provides generative AI photo-editing and design capabilities to consumers and businesses, uses Veo 2 and Imagen 3 to improve the quality of its offering and accelerate its development.
• Prodia offers APIs to integrate generative AI into creative tools. Built on Google Cloud, Prodia relies on GPUs & DWS to serve the fastest text-to-image and instruct-to-edit models in the world, as verified by Artificial Analysis benchmarks. Prodia uses Veo 3 and Nano Banana to further power multimodal AI features.
• Reclip, a “real” social media application, leverages GCP’s Generative Media tools (Veo, Imagen) to create short, engaging animated videos from real time audio clips, captured by their proprietary app. Consumers love sharing these precious, funny and real “Reclips” with their friends and family.
• Scope3 is enhancing its ad-tech platform with AI-powered features, using Gemini 2.5 Flash to offer features like real-time content classification, ensuring content is aligned with brand preference.
• Spot AI, a video AI agent builder, leverages Google Cloud PubSub to turn security cameras into intelligent agents to enhance safety, security, and operations without needing AI/ML teams.
• Wondercraft, an AI-powered content studio that helps users create engaging audio ads, podcasts and more, is leveraging Gemini models for some of its core functionalities and will soon release a Veo 2 integration.
• Writer, an enterprise generative AI platform, builds and trains its 17-plus LLMs on Google Cloud using Google Kubernetes Engine and high-performance NVIDIA GPUs. This allows the company to scale efficiently and cost-effectively, delivering fast, low-latency answers for enterprise customers who demand accurate and on-brand AI-generated content.

• AndesML, a retail media platform, helps large enterprises launch and monetize their own ad networks by showing the right ad to the right customer at the right time. Built on Vertex AI, BigQuery, and Gemini models, the AndesML platform has delivered a 30% performance lift in customer campaigns, accelerated production time by more than 30 days, and reduced operational costs.
• Audiomob, an in-game audio ad platform, replaced its legacy business intelligence system with BigQuery and Looker to gain real-time insights from its global data. This move enabled the company to handle billions of monthly transactions, contributing to triple-digit yearly revenue growth and significant savings in engineering time.
• Hedra, an end-to-end marketing creation platform, is designed to generate high-quality content at scale. Hedra Studio combines its proprietary multimodal models with other leading models like Veo and Imagen, enabling users to produce polished marketing content for any use case. Hedra’s Live Avatars use Gemini to deliver dynamic, real-time interactive video experiences.
• Inworld, an AI platform for builders of consumer applications, uses Google Cloud and Gemini to cost-effectively handle tens of millions of concurrent users with response times measured in milliseconds, meeting strict requirements for quality, cost control, and security.
• Koolio.ai helps creators produce high-quality podcasts and audio content. Koolio.ai integrates Gemini, Lyria, and Veo to power features such as AI-generated dialogue, accurate transcription, intelligent sound effects and music selection, and audio enhancement, streamlining the entire audio creation workflow from concept to final production.
• MNTN uses Google Cloud to power its Connected TV ad platform, making TV campaigns as measurable as search or social. With AI-driven tools like MNTN Matched and Security Command Center, MNTN scales creative and targeting securely and at speed.
• Napster, a metaverse company, is building a no-code 3D e-commerce platform on Google Cloud using Vertex AI and Gemini. This supported 20-85% infrastructure cost reductions and saved over 3,600 developer hours, making immersive 3D web experiences accessible and affordable for its customers.
• Potrero Labs, a creator-focused platform, has launched Jams, an AI-first video social network empowering authentic self-expression. Its platform simplifies video creation, allowing users to record short videos and let Jams enhance them. Jams offers a simple UI with a variety of models under the hood, including Gemini 2.5 Pro for script creation, multi-modal Gemini for video analysis, and Veo 3 for backgrounds, b-rolls, and audio.
• Producer.ai (formerly Riffusion), an AI music platform, trains generative music models and builds products that empower anyone to create the music they imagine. “The Producer” music collaboration agent helps users create original, studio-quality songs from text, audio, or visual prompts. Gemini on Vertex AI assists with prompt augmentation and data pipelines, while Vertex AI APIs offer access to advanced multimodal models for experimentation.
• Rembrand is an AI-powered advertising platform that facilitates in-video product placements for content creators and advertisers on social media and CTV. Powered by Google Cloud’s AI Infrastructure, Rembrand enables brands to genuinely connect with audiences without disrupting the content.
• Satisfi Labs will begin using Gemini models to power a new agentic platform for hundreds of customers in sports, entertainment, and tourism. The Agentic Platform delivers specialized agents for guest experiences, ticketing, on-site, safety, and merchandise tuned by industry experts to help live experience businesses sell more, service faster, and gain real-time insights from every guest conversation
• Scorpion, a digital marketing company for SMBs, uses Google’s VEO AI to scale video ad production. By integrating this technology into its toolkit, Scorpion makes creating professional videos for websites and advertising faster and more accessible for all businesses.
• StatusPro builds NFL virtual reality experiences for gaming and training and is now developing its newest game on Google Cloud, including a new Gemini-powered in-game coach.
• Synthesia, an AI video enterprise platform, helps businesses create instructional videos for employee training, customer support, sales enablement, and product marketing. The company is using Veo 3 to contextually adapt visuals to the content delivered by its AI avatars and voices.
• Tinuiti, a performance marketing agency, used Google’s VertexAI to develop an AI-powered service that develops and optimizes ad copy to increase performance. The tool embodies a philosophy of maximizing growth by minimizing waste, and a recent experiment showed significant ROAS performance improvements compared to human-curated copy.
• Toonsutra, an India-based webcomic platform, is using Google’s Gemini AI to go global. By making stories accessible in regional languages and adding Lyria 2 for music, Gemini for voices, and Veo 3 for animation, they’re creating next-gen immersive comics.
• Velin.ai, a content creation platform for small businesses, offers an AI agent that explains the content and its underlying strategic implications while acting as a unified content workspace. Gemini 2.5 drafts everything from scripts to social campaigns, while Imagen 4 and Veo 3 generate aligned visuals and video clips, ensuring a consistent brand narrative across all content.
• Visla is an AI-powered video creation platform that helps businesses and creators produce pro videos in minutes. Using Google’s Imagen 4, Gemini Flash Image 2.5, Veo 3, and Visla’s AI Video Agent with Avatars, it adapts visuals, narration, and automates polished content for learning, training, and marketing.

• LitLab.ai, a reading platform, leverages Veo3 and Vertex AI to generate personalized, curriculum-aligned stories and provide real-time oral reading analysis. They create decodable content and employ voice recognition for instant teacher feedback on student fluency.
• Savvy revolutionizes learning by automatically generating flashcards and quizzes from PDFs, notes, videos, and podcasts. As students answer, Savvy leverages Gemini to dynamically grade their answers, providing instant feedback and personalized learning.
• Studyhall AI, an AI research platform, graduated from Google Cloud’s UK Growth Accelerator program and built a mobile application that uses Gemini models to help coach students on reading, writing, and exam prep.
• Subject.com, an AI-powered platform for grades 6-12, blends cinematic storytelling with superintelligent AI so students and teachers never get stuck. VertexAI, CloudSQL & BigQuery power Subject’s teacher assistant tool Spark, instant feedback, “ExplainThis” text simplifier, 24/7 Homework Helper, and personalized learning tied to student interests.

• Deeli AI, an AI-powered platform, helps companies discover and evaluate emerging technologies to make informed investment decisions. The company builds its product and data pipeline on various services such as GCE, Cloud Run, and Dataflow, and uses models from the Vertex AI Model Garden.
• Nectar’s AI-driven community agents with Gemini to handle customer conversations on social platforms, influencer marketing, and real-time product feedback at scale for leading brands & retailers. By transforming unstructured social data into actionable insights and powering customer conversations, Nectar helps brands deepen relationships and drive measurable growth.
• Simbe, a multimodal, retail-focused computer vision company, built its AI-powered Store Intelligence platform on Google Cloud. By deploying autonomous robots and sensors, Simbe provides real-time insights into shelf inventory and price accuracy. This helps retailers reduce out-of-stock instances, improve pricing and promotion execution to the high 90% range, and achieve a 4x return on investment within 90 days.
• Zapia AI, a retail technology company, uses AI agents to support millions of users with product discovery, local business searches, and purchase assistance, resulting in over 90% positive user feedback. Its multi-agent orchestration is powered by Gemini to improve agent reasoning, reduce latency, and lower operational costs.
• Zazzle is a global platform for custom products and designs made on demand. Zazzle uses Gemini ADK and CCaaS to facilitate chat-based product discovery and enhance customer experience, making it easier to find the right designs across a wide range of products.

• Aptori, an AI security company, detects vulnerabilities in AI-generated code, prioritizes risks, and automates code fixes in real-time. Aptori uses Gemini to analyze code for security weaknesses and generate context-aware fixes, integrating its AI Security Engineer directly into developer workflows.
• Chainguard, a software supply chain security company, uses Google Cloud Run and Google Kubernetes Engine to provide developers with secure open-source building blocks. Its serverless architecture streamlines operations and product development, reducing infrastructure management costs and enabling them to scale effortlessly to meet increasing user demand.
• Eon, a cloud data protection platform, uses Google Cloud Storage and BigQuery to transform backups into AI-ready data lakes. This allows its customers to eliminate fragmented data silos, reduce secondary storage costs by up to 98%, and improve data recovery times by up to 90%.
• Galileo, an AI observability and evaluation platform for building trustworthy AI applications, addresses the critical challenge of mitigating LLM unpredictability and hallucinations. Using Gemini to build its “evaluation agents” and running on a scalable Google Cloud infrastructure with NVIDIA GPUs, Galileo provides a holistic “trust layer” for reliable AI. This has enabled customers to de-risk over 1,000 AI applications, while go-to-market support from the Google for Startups Cloud Program helps Galileo accelerate growth and unlock new opportunities.
• Prediction Guard is using Google Cloud services like Confidential Computing and Vertex AI to support its platform for added gen AI safety.
• Resistant AI, an AI-powered security company, uses Google Cloud to build solutions that combat fraud in financial services documentation and workflows. Running on Google Cloud infrastructure, the company’s specialized document fraud detectors scrutinize financial documents in 500 different ways, helping to protect automated workflows like those using Google’s Document AI from sophisticated financial crime.
• Specular, an offensive cybersecurity platform, builds AI agents using Gemini 2.5 Pro to automate attack surface management and penetration testing. Their platform automates traditional workflows to identify, assess, and remediate cybersecurity, helping enterprises proactively prioritize and respond to threats.
• Wyze Labs is rolling out new AI-powered anomaly detection features for its security camera systems, powered by Google’s vision AI tool.
• Zefr, a global leader in responsible AI, powers Fortune 500 brand advertising with safety and suitability on platforms like YouTube and TikTok. Using patented Cognitive AI with Gemini Flash and Vertex AI, Zefr analyzes video, image, audio, and text to deliver trusted, scalable solutions.

• aSim, an AI-powered mobile app development tool, allows you to quickly generate, share, and discover mini-apps. Users can instantly generate an app from a prompt, leveraging APIs/LLMs like Google Maps and Gemini, as well as image and video generation from Nano Banana and Veo 3.
• Bud Financial, a data intelligence provider focused on banking clients, leverages DataStax Astra DB on Google Cloud with Gemini. The platform enables ultra-fast processing of complex financial data, helping clients reduce fraud by over 90% and shortening the time required to access critical data analytics from weeks to minutes.
• Bynry’s SMART360 leverages Google Cloud’s robust infrastructure to empower small and mid-sized utilities to enhance operational efficiency and customer satisfaction.
• Citylitics, a predictive intelligence platform, transforms public infrastructure investment for municipalities, utilities, and engineering firms. By automating data processing with Dataflow and Cloud Run, it cuts analysis time by 71% and boosts data sources by 400%, helping customers proactively identify and win new business.
• ContextQA, an Agentic AI software testing platform, enables accurate, user-centric test automation from development start. The platform uses Gemini models to compare application behavior with expected outcomes, adapting automatically to changes.
• Flockx, an AI-powered event app, migrated to Google Cloud to support its growth and control costs. Using Google Kubernetes Engine and autoscaling on Compute Engine, the company accelerated product development and successfully demonstrated scalability by processing over 100,000 AI runs in a single weekend.
• Macro, an AI productivity platform, uses Gemini to modernize knowledge work by offering a unified workspace with features like multi-document chat and editable mind maps. The platform simplifies complex workflows and scales with demand for over 125,000 users in legal, finance, and education, while offering enterprise-grade security, data privacy, and compliance.
• MaestroQA, a conversation analytics data platform, is leveraging Gemini to enhance its AI-powered conversation analytics. By using Gemini, MaestroQA is improving its ability to analyze customer interactions across every channel, providing deeper insights that help businesses boost customer satisfaction and drive growth and retention.
• MLtwist, an AI data pipeline services company, processes, transcribes, translates, and labels large, complex data streams for enterprise applications. It uses Gemini and AI Studio for transcription and labeling tasks, saving approximately 63% of the time required to process even highly illegible documents.
• Moii.AI, a vision AI startup, uses Gemini and BigQuery to analyze CCTV footage for safety and productivity insights. This approach reduced video review time from days to minutes, saved the company $10,000 monthly on AI processing costs, and doubled its engineering team’s efficiency.
• Owl.AI, a sports technology company, delivers AI-powered solutions to professional sports leagues. Their offerings, which include judging and scoring, aim to enhance accuracy, consistency, and eliminate bias. Owl.AI achieves this by leveraging AI models built on Gemini and fine-tuned on Google Cloud to analyze real-time video footage of athletic performances.
• Provenbase has built its talent recruitment tool for businesses on Google Cloud and is now powering its transformative Deep Search for talent feature using Google Cloud AI.
• SandboxAQ is expanding its usage of Google Cloud and running a new AI drug discovery simulation platform on Google Cloud.
• Satlyt, a space compute leader, enables in-orbit AI workloads by orchestrating intersatellite communication and routing. It uses Google Cloud’s Kubernetes Engine, Vertex AI, and scalable data infrastructure to deploy AI agents and plans to deploy Google’s Gemma models in orbit.
• SE3 Labs, a 3D computer vision and AI company, uses Cloud Run to deploy advanced AI model technologies that create “Spatial GPTs,” which are essentially AI models that can understand and interact with the world in 3D.
• Temporal, a durable execution platform for developers, uses Vertex AI to enhance its customer support operations. The solution provides improved visibility into support trends by automatically categorizing 80% of support tickets, allowing the team to anticipate customer needs and identify new opportunities.