Why not? Just two words, but those two words challenge everything and can change anything. Why not help find a cure? Bring it here and even there. Wait, really? Yes, really. We're building the most helpful AI so you can turn an idea into an enterprise. Get the right crops into this box and breakfast on the table. Inspect 800,000 packages a day and help protect our power grids. Because once we turn this into that, we ask, what else can we do? Find out where the wild things are, wilder. Spot patterns in crime data, catch phishing attacks, take 1,000 customer service calls an hour. Help coders, well, code. Let's make it happen.
Please welcome CEO of Google Cloud, Thomas Kurian.
Wow. Hello, everyone. Welcome to Google Cloud Next. Just one year ago, we stood here and talked about the future of AI for organizations. Today, that future is being built by all of us. In 2024, we shipped more than 3,000 product advances across Google Cloud and Workspace. We expanded Google Cloud to 42 regions, including Sweden, Mexico, and South Africa, and are rapidly expanding to countries like Malaysia, Thailand, and Kuwait. We expanded our 2 million miles terrestrial and subsea fiber network by announcing new subsea cables like Umoja, Bosun, and Proa. Google's AI momentum is exciting. We're seeing more than 4 million developers using Gemini, a 20x increase in Vertex AI usage last year, driven by the strong adoption of Gemini Flash, Gemini 2.0, Imagen 3.0, and most recently, Veo, our advanced video generation model. Over 2 billion AI assists monthly to business users right within Google Workspace.
Even more exciting is the momentum with you, our customers. Here at Next, we'll be sharing over 500 customer stories, showcasing real business innovation impact from AI adoption. Google is building for a unique moment. We're investing in the technology and the ecosystem to power your growth and transformation. Let's hear more from a special guest. A warm welcome for the CEO of Google and Alphabet, Sundar Pichai.
Thank you, Thomas. Good to be with you all here in Vegas. Last year, I joked in my remarks about how I was auditioning for The Sphere. It turns out I got the gig. Last night, I was on stage at The Sphere to share a new collaboration. We are introducing "The Wizard of Oz" to a new generation using Google AI, transforming one of the greatest films of all time for one of the largest screens in the world. It is a huge ongoing effort and not something we could have attempted even 18 months ago. It shows how rapidly technology is evolving and how it can enable us to rethink what is possible. I think that is a fitting theme for Cloud Next. The chance to improve lives and reimagine things is why Google has been investing in AI for more than a decade.
We see it as the most important way we can advance our mission, to organize the world's information and make it universally accessible and useful. With Google Cloud, we see AI as the most important way we can help advance your mission. The opportunity with AI is as big as it gets. That is why we are investing in the full stack of AI innovation, starting with the infrastructure that powers it all. We are making big investments now and for the future. In 2025, we plan to invest around $75 billion in total CapEx. This investment will be directed towards our servers and data centers, which includes powering our AI compute and cloud business. This will greatly benefit our customers like all of you. We need our infrastructure to move at Google speed with near-zero latency, supporting services like Search, Gmail, and Photos for billions of users worldwide.
We use it for training our most capable model, Gemini. Google's backbone network is unparalleled, as Thomas just mentioned, spanning more than 200 countries and territories, powered by over 2 million miles of fiber. Today, I'm pleased to announce that we are making Google's global private network available to enterprises around the world. We call it Cloud Wide Area Network, or WAN. Cloud WAN leverages Google's planet-scale network. It's optimized for application performance and delivers over 40% faster performance while reducing total cost of ownership by up to 40%. Companies like Citadel Securities and Nestlé are already using this network for faster, more reliable solutions. It'll be available to all Google Cloud customers later this month. This builds on our legacy of opening up our technical infrastructure for others to use. We do this with our custom AI chips called Tensor Processing Units, or TPUs.
Since 2013, we've invested heavily in this specialized hardware. We continue to make massive improvements in performance and efficiency at scale. Today, I'm proud to announce our seventh-generation TPU, Ironwood, is coming later this year. Compared to our first publicly available TPU, Ironwood achieves 3,600x better performance, an incredible increase. It's the most powerful chip we have ever built and will enable the next frontier of AI models. In the same period, we've also become 29x more energy efficient, and Amin will share more later today. This progress is laying the foundation for breakthroughs across multiple fields. Quantum computing is a great example. Our newest quantum chip, Willow, cracked a key challenge in quantum error correction that has eluded researchers for three decades. It can reduce errors exponentially as we scale up using more qubits.
The Willow chip really paves the way for a useful large-scale quantum computer down the road. Our infrastructure enables the next layer of the stack, research and model. Over the last decade, our research teams have pushed the boundaries of AI forward. Today, they are accelerating science and discovery, from our AlphaFold breakthrough with protein folding to WeatherNext , our state-of-the-art weather forecasting models. World-class research is what enables us to push the frontier with our Gemini models. In December, we introduced Gemini 2.0 with new advances in multimodality, like native image and audio output, as well as native tool use. This new generation has also pushed the frontiers of another capability called thinking. A couple of weeks ago, we released a new model, Gemini 2.5, a thinking model that can reason through its thoughts before responding. It's our most intelligent AI model ever.
It is the best model in the world, according to the Chatbot Arena Leaderboard. It is state-of-the-art across a range of benchmarks requiring advanced reasoning. That included the highest score ever on Humanity's Last Exam, one of the hardest industry benchmarks that is designed to capture the human frontier of knowledge and reasoning. There is a lot of impressive words, but let me show you what it can do. Take a look at this Rubik's Cube coded by developer Matt Berman. You might think of it as a toy, but it is actually a really complex reasoning challenge. Adjustable dimensions, scrambling the squares, keyboard controls, and Gemini 2.5 Pro can simulate it all. It is a significant leap and shows the ability to produce robust, interactive code. That is a fun one. Let's look at one other example.
With a series of prompts, developer John Morden used 2.5 Pro to create a series of physics simulations, like the Earth's magnetic field and general relativity. You can see how the model turns really complex concepts into stunning and interactive visuals. These are just a few brief examples, but we are excited about the possibilities, and we can't wait to see what you'll build with it. Gemini 2.0 is now available for everyone in AI Studio, Vertex AI, and in the Gemini app. I'm also excited to announce Gemini 2.5 Flash, our low-latency and most cost-efficient model with thinking built in. With 2.5 Flash, you can control how much the model reasons and balance performance with your budget. 2.5 Flash is coming soon in AI Studio, Vertex AI, and in the Gemini app. We'll be sharing more details on the model and its performance soon.
I'm pretty excited by it and can't wait for you to see it for yourselves. Our goal is to always bring our latest AI advances into the fourth layer of our stack, products and platforms. Today, all 15 of our 500 million user products, including seven with 2 billion users, are powered by our Gemini models. AI deployed at this scale requires world-class inference, which enterprises can benefit to build your own AI-powered applications. Gemini is also helping us create net new products and experiences. NotebookLM is one example, now used by over 100,000 businesses. It uses long context, multimodality, and our latest thinking models to show information in powerful ways. Gemini is not our only industry-leading model. Veo 2 is the leading video generation model.
Major film studios, entertainment companies, as well as the top advertising agencies in the world, are using it to bring their stories to life. Getting advances into the hands of both consumers and enterprises is something we are really focused on. This is why we are able to innovate at the cutting edge and push the boundaries of what's possible for us and for you. The result: better, faster, and more innovation for everyone. It's exciting to see how that's helping companies of all sizes do more with AI and translate those benefits to customers. I'm delighted to introduce Chris Kempczinski, CEO of McDonald's, to tell you more. First, thank you for having me, and enjoy a week together in Las Vegas. Over to you, Chris.
McDonald's is undergoing a once-in-a-generation transformation. We have about 65 million people that come to our restaurants every single day. It is how do we make their experience even better? Google's a big part of that, particularly as more and more of those customer interactions are happening in a digital world. That is why we're transforming our restaurant experience with the help of Google Cloud. Behind the counter, our restaurant team's jobs are becoming increasingly complex. With edge computing from Google Distributed Cloud, capabilities will readily improve stability, security, and performance in our restaurants, all while giving us the space and power to test several new concepts we were not able to do previously. For example, shift leaders will be able to leverage an AI-powered assistant to help spot issues in the restaurant quickly.
Our restaurant managers will be able to receive alerts on their devices based on real-time data, say, from their freezer or fryers, along with guidance for predictive maintenance. With Gemini on Vertex AI, we can centralize all this information from restaurants in real- time, making it easier for the right people to get answers with a simple question or prompt, improving the work environment in our restaurants across the globe for our more than 2 million team members. That's the magic. That's the power of AI and what Google Cloud has brought to McDonald's.
Thank you, Chris. McDonald's is a great example of a company integrating AI into the very core of its operations. Customers around the world are choosing to work with Google for three important reasons. First, Google Cloud offers an AI-optimized platform with leading price, performance, precision, and quality. New today, everything you need to build and manage multi-agent systems. Our AI platform offers advanced infrastructure and databases, world-class research-leading models, and grounding for model responses with Google quality search. Vertex AI, a robust developer platform, including the broadest range of enterprise-ready tools with which you can build AI agents and enable a multi-agent ecosystem, and the most comprehensive portfolio of purpose-built agents.
Second, Google Cloud offers an open multi-cloud platform that allows you to adopt AI agents while connecting them with your existing IT landscape, including your databases, your document stores, enterprise applications, and interoperating with models and agents from other providers. You get value faster from your AI investments. Third, Google Cloud offers an enterprise-ready AI platform built for interoperability. It enables you to adopt AI deeply while addressing the evolving concerns around sovereignty, security, privacy, and regulatory requirements. You can adopt AI while we protect your data and your intellectual property and enable you to maintain compliance. Powering this offering is our advanced infrastructure core for AI. To share the latest, please join me in welcoming Amin Vahdat.
Thank you, Thomas. Demand for AI compute for training and inference is growing at an unprecedented rate. For over eight years, it has increased by over 10x year- over- year, a factor of 100 million in just eight years. We're continuing to offer leading power efficiency, performance, and networking for training and inference workloads, starting with the hardware. Today, we introduced our seventh generation of TPUs, Ironwood. Ironwood TPUs are our largest and most powerful TPU pods to date, more than a 10x improvement from our most recent high-performance TPU, with over 9,000 chips per pod, to meet the exponentially growing demands of the most demanding thinking models like Gemini 2.5. This delivers a staggering 42.5 exaflops of compute per pod. To give you a sense of the scale, the world's number one supercomputer supports 1.7 exaflops. Ironwood pods offer more than 24x that compute power. Ironwood TPUs are truly built for the next generation of AI workloads.
TPUs are an incredible achievement, but they are just one piece of our overall infrastructure. After all, a chip is only as powerful as the system that surrounds it. Our AI Hypercomputer is a supercomputing system designed to simplify AI deployment, improve performance, and optimize costs. It supports the best hardware platforms and brings together a single unified software stack and consumption model that enables you to use the hardware that best meets your needs and easily transition from one hardware generation to the next. Vital, as we innovate so rapidly. We have enhanced our GPU portfolio with the availability of A4 and A4X VMs , powered by NVIDIA's GB200 and B200 Blackwell GPUs. We were the first cloud provider to offer both options.
We're also pleased that Google Cloud will be among the first to offer NVIDIA's next-generation Vera Rubin GPUs, which offer up to 15 exaflops of FP4 inference performance per rack. We also introduced Cluster Director, which enables you to deploy and manage a large number of accelerators as a single unit of compute to improve performance, efficiency, and resilience. Storage is also vital to reduce the bottlenecks for training and inference. We're introducing new storage innovations. Hyperdisk Exapools offer the highest aggregate performance and capacity per AI cluster of any hyperscaler. Anywhere Cache keeps data close to your accelerators with up to 70% improvement in storage latency to reduce training time. Rapid Storage, our first zonal storage solution, offers 5x lower latency for random reads and writes compared to the fastest comparable cloud alternative. Software is how we orchestrate and simplify access to this powerful hardware.
Today, we're introducing three enhancements for AI inference. First, we're introducing new inference capabilities in Google Kubernetes Engine, including GenAI-aware scaling and load balancing features, which help reduce serving costs by up to 30%, tail latency by up to 60%, and increase throughput by up to 40%. Second, we're announcing that Pathways, Google's own distributed ML runtime powering Gemini, is now available for the first time for cloud customers. Developed by Google DeepMind, Pathways enables state-of-the-art multi-host inferencing for dynamic scaling with high performance at optimal costs. Now you can scale out model serving to hundreds of accelerators for the best combination of batch efficiency and low latency. Third, we're bringing vLLM to TPUs. This allows customers who optimize PyTorch with vLLM for GPUs to easily and cost-efficiently run their workloads on TPUs.
All of these AI Hypercomputer hardware and software enhancements together enable us to deliver more intelligence or useful AI output at a consistently low price. This is one reason why Gemini 2.0 Flash, powered by AI Hypercomputer, achieves 24x higher intelligence per dollar compared to GPT‑4o and 5x higher than DeepSeek R1. We are truly seeing tremendous momentum across our AI infrastructure portfolio, tripling the number of TPU and GPU hours consumed by our cloud customers just over the past year. We are seeing tremendous customer momentum with AI unicorns like Anthropic, Anyscale, Arize, and Contextual AI. Enterprises: Toyota deployed ML models for factory workers. Schrödinger uses cloud GPUs for advanced drug discovery. TSMC protects its critical data for mission-critical workloads. Airbus deployed an AI platform to advance aircraft performance, safety, and reliability.
Beyond optimizing training and inference in the cloud, we know that many AI workloads need to be run on-premises. As you heard from Chris Kempczinski at McDonald's, Google's Distributed Cloud brings our hardware and software to your environments so you can bring AI capabilities closer to where data is generated for low latency and highly sensitive data in particular. Today, we are announcing that Gemini can run on Google Distributed Cloud locally in air-gapped environments, as well as connected environments. This all comes with the support for NVIDIA's confidential computing and Blackwell systems, DGX B200 and HGX B200 platforms with Dell as a key partner. This complements our Google Distributed Cloud air-gapped product, which is now authorized for U.S. government secret and top secret missions, and on which Gemini is now available, providing the highest levels of security and compliance. NVIDIA is an important partner for Google and our customers.
Let's hear directly from CEO Jensen Huang.
Building advanced AI infrastructure is deep computer science. No company is better at every single layer of computing than Google and Google Cloud. Between NVIDIA and Google Cloud, this super partnership includes capabilities that cover literally every single layer and every single aspect of computing. Every industry, every company, every country wants to get their hands on AI. However, everything has to be fundamentally confidential and secure. We are announcing something utterly gigantic today. Google Distributed Cloud with Gemini and NVIDIA are going to bring state-of-the-art AI to the world's regulated industries and countries. Now, if you can't come to the cloud, Google Cloud will bring AI to you.
Thank you, Jensen. You know, we really value our deep engineering relationship with NVIDIA. Building on the groundbreaking research of Google DeepMind, we're delivering rapid innovation across many AI models, starting with Gemini, our most capable family of AI models. In the last year alone, we released Gemini, our first native multimodal model. We delivered the first 2 million token context window. We built the live API for live bidirectional voice and video interaction, led in price performance with our flash models. We recently launched Gemini 2.5 Pro, which is state-of-the-art on a wide range of benchmarks. I'm pleased to say number one on Chatbot Arena. Gemini is providing best-in-class AI for many companies around the world, including our close partners, Box and Palo Alto Networks, who are using Gemini 2.5 to deliver new applications.
It's also integrated across our own products, including Google Workspace, where Gemini powers features in Gmail, Docs, Drive, and Meet, and is now included in all subscriptions. Gemini and Workspace is helping customers like EV manufacturer Rivian, Freshfields, to enhance legal work and expedite tasks like document drafting and research, and companies of the Schwarz Group, Europe's largest retailer. Today, I'm pleased to announce three new innovations with Gemini and Workspace. Help Me Analyze in Google Sheets, which guides you through your data to complete expert-level analysis. Audio Overviews in Google Docs, where you can interact with Docs in an entirely new way by creating high-quality audio versions of your content. Google Workspace Flows help you automate time-consuming, repetitive tasks and to make decisions with more context. Let's see how Google Workspace is helping businesses around the world.
We are scattered all over the globe. It's just bonkers to try to get everyone to collaborate. Keeping up with my email has always been really, really difficult. Is there anything more intimidating than a blank white page? Where do you begin? It's more important than ever that you have tools to work more quickly and efficiently together. Using Help Me Write, we were able to save 35 hours a month for product descriptions for our website. We are leveraging Meet to take notes, summarize them, and generate action items after the meeting so that we can be really present and focus on the content.
When you're developing a deck or a pitch for a client and you're coming up with ideas and you need to visually manifest those ideas, that used to take days, and now with the right prompts, we can do that in hours. We have to worry less about security because we know Google has our back. Security played a big part of the decision to move from the legacy on-premise tool set to Google Workspace. The impact of Gemini for Workspace in our business has been really transformative.
Beyond Gemini, over the last year, we've made huge improvements to Imagen 3, our highest quality text-to-image model, which generates images with better detail, richer lighting, and fewer distracting artifacts than previous models. Imagen delivers accurate prompt adherence, bringing your creative vision to life with incredible precision. We also introduced Chirp 3 to help you create custom voices with just 10 seconds of input and to weave AI-powered narration into your existing recordings. Today, we're making Lyria available on Google Cloud to transform text prompts into 30-second music clips and we're the first hyperscaler to offer this capability. Let's hear a clip from Lyria. Veo 2. Veo 2 is our industry-leading video generation model. It generates many minutes of 4K video watermarked with SynthID to ensure they can be identified as AI generated.
It gives creators unprecedented creative control with new editing tools, including camera presets to direct shot composition and camera angles without complex prompting, first and last shot control to define the beginning and the end of a video sequence with Veo seamlessly bridging the gap, and dynamic inpainting and outpainting for video editing and scaling. With Gemini, Imagen, Chirp, Lyria, and Veo, Google is the only company that offers generative media models across all modality. All of them are available to you today on Vertex AI. We've seen great examples from our customers. Kraft Heinz is speeding up campaign creation. Agoda creates unique visuals of travel destinations. Bending Spoons makes 60 million photos every day more fun. L'Oréal Group generates diverse cinematic shots using our models. Please join me now in welcoming Nenshad Bardoliwalla for a demo of our models in action using Vertex AI.
Hello, everyone. How many of you have heard about our Cloud Next concert already? That's not as many I was hoping to hear about. I think that's because we've been missing a teaser video. Now, let me tell you, it wasn't easy to pick the artist this year because it turns out that even though he looks very demure and very mindful, Thomas Kurian is a massive Chappell Roan fanboy. Yes, I have seen the video that he sent Chappell directly of him going, "H-O-T-T-O-G-O, Thomas wants you in the show." Yeah. We waited for weeks to get a response from Chappell. She broke Thomas' heart with just three words. Good luck, babe. We're going to use Vertex Media to pump Thomas up and create a teaser video that's going to get you as amped up as I am. We've already created our final video.
I'm just going to show you how we got there. Given where we are, we're going to use Las Vegas skyline as a perfect backdrop for what we're going to do with Vertex AI Media Studio. Let's go ahead. We're going to start by bringing in the Las Vegas skyline image. Really high-quality, beautiful image. We're going to generate video. Here's the new hotness. Check it out. Camera presets built right into Veo. Panning left, panning right, time-lapse, tracking shots, and even drone shots. Let's go ahead and submit a drone shot of the city skyline. There we go. We'll go and submit this. Now, normally, this would take a few seconds. I ran this earlier today, so it's cached. It's going to be a little quicker than normal. All right. Let's look at video number one. Absolutely spectacular.
We have the ability to see the fountains, the Eiffel Tower. Now, let's go ahead and take a look at video number two. A different angle that Veo creates for us. Again, stunning imagery. You can see the clouds in the background. Look at the cars driving up and down Las Vegas Boulevard. Absolutely incredible. Now, one video is not going to do it for the concert promo we want to do. I want to show you some of the other videos that I created. I have one here of the stage being set up all through the power of Veo. I have one of the band. I even have one of the audience actually clapping for what they're about to see. This will be a good reminder for all of you. Now, something very interesting happened.
It turns out that Veo can do something that my 12-year-old can do. That is be an expert in photobombing. It turns out that this great video we just saw has a crew member. We love our crew members. However, in this case, I'd like to feature the guitar because the guitar is the most important part of the band. Let's go ahead and use Veo's new inpainting capability. I'm sorry, sir. I apologize. I know you're very good at your job. I am going to have to remove you from this image. We will send flowers to you and your family, though, sir. Let's use the new inpainting capability. Wait a couple of seconds. Let's see what we see. Now, if this does what I think it does, it should preserve every single aspect of what we saw before just without our stagehand.
Look at that. OK. So we got some video clips. Now we need some music. Let's try the first clip I created with Lyria and see how we like it. You know, that's not quite my tempo. I need music that's going to make all of you feel like I'm never going to give you up. I'm never going to let you down. I'm never going to run around and desert you. Let's try clip number two and see how that works. All right. We have the recipe. I like that tune better. We've got the videos. We've got the music. Let's pull it all together and see what it looks like. Here we go. Play it, Sam. What do you think? Absolutely amazing.
We've seen the amazing capabilities of Veo, the ability to create incredible shots with very little prompting, the ability to have editing capabilities that are easy to use, and the cinematic quality. We're going to see you tomorrow night when Thomas does a stage dive into the mosh pit at Allegiant Stadium for the Killers. Welcome back to the stage, my friend and spiritual advisor, Thomas Kurian.
Thank you, Nenshad. I am also very excited for the concert tomorrow night. We're also bringing AI models to the physical world. Our partners like Samsung are using Gemini models for their exciting new AI companion robot, Ballie. Google DeepMind recently introduced two new AI models for a new generation of helpful robots. Now, let's talk about Vertex AI, a comprehensive AI platform. Vertex helps you discover enterprise-ready foundation models to customize, evaluate, and deploy applications built with the best foundation models and to build and manage AI agents at scale. Let's hear how Intuit is making tax preparation even easier with Document AI, which is part of Vertex AI.
Last year, Intuit TurboTax processed 44 million returns and $107 billion in refunds with the help of AI. Yet some customers with complex 1099 forms faced hours of manual data entry. This year, Intuit unlocked higher-quality data comprehension and autofill with Google Cloud Document AI. This done-for-you experience simplifies tax filing for millions, freeing up time for living life. Intuit builds a new way to make taxes easier.
Tens of thousands of companies are building with Vertex AI and Gemini. Nokia built a tool to speed up application coding and development. Wayfair updates product attributes 5x faster. AES, an energy company, reduces audit costs by 99% and audit time from 14 days to just one hour. Commerzbank is creating AI-assisted summaries of investment advisory calls. Seattle Children's Hospital makes thousands of pages of clinical guidelines instantly searchable by their pediatricians. United Wholesale Mortgage is transforming the mortgage experience, more than doubling underwriter productivity. Honeywell has incorporated Gemini into their product development.
Honeywell and Google Cloud designed a new way to manage product lifecycles. It will revolutionize how they handle millions of products. Built with Vertex AI, BigQuery, and Gemini, this agentic framework accelerates spec and model creation, connects with their global install base to uncover performance improvement insights, and extends lifecycles by re-engineering products, estimated to help their engineers deliver results up to 70% faster. With AI agents, Honeywell is introducing a new way to optimize millions of products.
In just the last year, we've seen over 40x growth in Gemini use and Vertex AI, now with billions of API calls each month. Vertex AI gives you easy access to over 200 curated foundation models through our model gardens. We offer all of Google's models: Gemini, Veo, Imagen, and our latest research models, curated popular third-party models, and open-source models, all now on Vertex AI. New Vertex dashboards help you monitor usage, throughput, latency, and to troubleshoot errors. New tuning methods help you optimize the model's performance for your applications. We are excited to announce the general availability of Meta's Llama 4 on Vertex AI. Last week, we announced that AI21 Labs' full portfolio of open models are also accessible on the Vertex AI model garden. With Vertex AI, you can be sure your model has access to the right information at the right time.
You can connect to any data source or any vector database on any cloud. Announcing today, you can build agents directly on our existing NetApp storage without requiring any data duplication. You can connect to a broad range of applications, including Oracle, SAP, ServiceNow, and Workday. For model factuality, we offer the most comprehensive approach to grounding on the market today, combining grounding with Google Search, grounding with your own enterprise data, Google Maps, and third-party sources. Let's hear from Deutsche Bank CEO Christian Sewing.
For over 150 years, our clients have looked to Deutsche Bank to support their lasting success and financial security. They need us now more than ever as advisor and risk manager in a world marked by uncertainty and shifting geopolitics. Technology plays a key role. Our partnership with Google Cloud enables us to take advantage of the latest tools.
DB Lumina is our AI-powered research agent built on Gemini and Vertex AI. It maintains data privacy and improves our productivity while operating in one of the most regulated industries, where trust is built in years and lost in seconds.
A tool like DB Lumina allows us to be ahead of our competitors and provide faster, more accurate analysis of data. Recently, there was a big report in the markets, which was 400 pages. We put it into DB Lumina and gave it some prompts. Within seconds, it gave us a three-page summary. We were able to give that to traders and our clients to help them process that information.
Through our partnership with Google Cloud, we have seen a real breakthrough. This is just the beginning. We see a future where generative AI is integrated into basically every process we run, making our employees' lives easier while meeting the changing expectations of our clients.
Thanks so much, Christian. We're thrilled to see how quickly you at Deutsche Bank have moved AI from pilot to production. Now, let's talk about agents. Agents are intelligent systems that show reasoning, planning, memory, and the ability to use tools. They're able to think multiple steps ahead, use tools, including working with software and systems, to get something done on your behalf and under your supervision. Agents work alongside employees to drive efficiencies, to help with decision-making, and increase innovation. A great example of a company working with Google Cloud to develop agents is Salesforce. Let's hear from CEO Marc Benioff.
Salesforce and Google, two of the world's most innovative companies. We've been on an incredible journey together. Today, that partnership has never been stronger. Right now, we are really at the start of the biggest shift any of us have ever seen in our careers. I'll tell you, that's why we are so excited about Agentforce and our expanded partnership now with Google. I just love Gemini. I use it every single day, whether it's Gemini inside Agentforce, whether it's all the integrations between Google and Salesforce. Together, we're leading the digital labor revolution. That's the future. It's going to drive massive gains in human augmentation and productivity, efficiency, the fundamental KPIs of our business, and ultimately, our customer success. We are looking forward to doing even more between Salesforce and Google.
Thank you very much, Marc. We're excited to build together and continue this journey with you at Salesforce. With Google Cloud, starting today, you can build and manage multi-agent systems with Vertex AI and our new agent development kit. You can scale the adoption of agents across your enterprise with our newly released Google Agent Space . You can accelerate deployment with packaged AI agents that are ready for use today. Following the introduction of Vertex AI Agent Builder last year, we're announcing today a new agent development kit. It is a new open-source framework that simplifies the process of building sophisticated multi-agent systems. Now, you can build sophisticated Gemini-powered agents, help them use tools, do complex multi-step tasks, including reasoning or thinking. You can also discover other agents, learn their skills, and enable agents to work together while maintaining precise control.
Agent Development Kit supports the Model Context Protocol, which provides a unified way for AI models to access and interact with various data sources and tools rather than requiring custom integrations for each and every one. We're also introducing a new agent-to-agent protocol that allows agents to communicate with each other regardless of the underlying model and framework they were developed with. This protocol is supported by many leading partners who share our vision to allow agents to work across the multi-agent ecosystem and with agents built on other agent frameworks, including LangGraph and CrewAI. Today, we're putting AI agents in the hands of every employee with Google Agent Space . Employees using Google Agent Space can now find and synthesize information from within their organization, converse with AI agents, and have these agents take action on their behalf for their enterprise applications.
Google Agent Space combines Google-quality enterprise search, conversational AI or chat, and Gemini and third-party agents. It also includes a broad set of tools, including purpose-built connectors to search and transact with documents and databases, as well as SaaS applications with advanced security and compliance to protect your data and your intellectual property. Let's take a look at Agent Space in action. Please welcome Gabe Weiss.
Thanks, Thomas. For the next few minutes, I'm going to be a relationship manager at a bank. Starting with a quick tour, this is my home page, authenticated and personalized just for me. The agent gallery lets me see my company's approved selection of purpose-built agents, including ones powered by third-party models like Llama and Claude. You see we've got some Google-made agents. We have agents that my bank has made available to me, either ones we've created or ones built by partners. The best part, my own personal agents, which I can build directly inside Agent Space with this button over here, or even easier just from having a little conversation. Let's see how easy it is to create an agent to automate a daily task. Now, it's critical for me to stay on top of what's going on with my clients.
I start every morning with a portfolio analysis. I'm going to use a clipboard because no one wants to watch me typing. Run an analysis of my client portfolio and identify potential risks and opportunities. This only uses information that I have permission to access. It knows which clients are mine and summarizes top points from my data sources like OneDrive, Salesforce, or Dun & Bradstreet. If I have questions, I have a direct link to my sources here. If I need even more control, I can refine that list of sources. Agent Space doesn't just summarize information. It's interpreting my question and surfacing what matters most. For example, in this chart, I can see Agent Space has flagged that Acme General Contracting might have some cash flow problems in the future.
Already, it's given me a massive report, which is going to save me a ton of manual research. I can go ahead and read this later. For now, let's set up an agent so I can keep an eye on Acme. Agent Space automatically generates an agent plan based on our conversation so far. This is good, but I think I want more. I'm going to have it generate an audio summary and send it to my inbox so I can listen to it on my morning commute. Just like that, I have built my own custom agent to use whenever I want without writing a single line of code. Now, Agent Space has identified a cash flow problem with Acme General Contracting. I need to dig into that. Maybe this is a problem with construction in general and not specific to Acme.
Agent Space has already identified that possibility as a suggested follow-up. Now, let's go ahead and deep dive into general contracting industry trends. This activates Google's enterprise deep research agent, which starts by telling me what it plans to research and in what order. At this point, I could edit this plan if I wanted to, but it looks pretty good. I'll start the research. I do want to call out, we've cached the plan and the results here. Normally, this would take a little bit longer. This agent is pulling in real-time information from Google Search to build its report. Even cooler, it's also searching my internal enterprise data and adjusting this plan in real- time, adding additional questions based on what it's going to find along the way. Again, an incredibly insightful analysis, including some source links.
Thankfully, here at the bottom, it also is going to give me a great succinct executive summary. Let's take a quick look at this. Yep, I can see Acme General Contracting is likely being affected by rising material costs, supply chain disruptions, and regulatory complexities that pose significant hurdles. That's really great. I mean, OK, maybe not for Acme, but the analysis is really great. I don't want Acme to be surprised by this at all. I am going to have our bank's cash flow agent do some forecasting across the next three quarters for me. This agent uses Google's new time series forecasting model, which is specifically trained for scenarios just like this. Again, I am going to get a super clear, very clear summary with, at the bottom, some great recommended steps for Acme. I need them to see it right away.
I can ask Agent Space, "Draft me an email to Acme General Contracting CEO requesting a meeting for next week." Just like that, I've got the draft ready to go. Even better, I can send it off directly from within Agent Space. I don't even have to switch to Outlook or Gmail. I'm all set. Agent Space has saved my session, so I can prep for that meeting right where I left off whenever I'm ready. Let's go ahead and recap. While I don't actually work for a bank, the value that Agent Space adds is very real. It's so easy to interact with all of your enterprise data and tools in one place and build and use agents directly from that conversational workflow.
Powered by Gemini 2.5 and Google Search technology, Agent Space is the only hyperscaler platform on the market that can connect to third-party data and tools and offers interoperability with third-party agents and models. For companies with strict regulatory needs, like a bank, Agent Space provides stringent access controls at the employee level and can operate within your own VPC, ensuring that your data stays yours while meeting all of your requirements. Agent Space is a game- changer. We can't wait to see how you all put it to work. Thanks. Back to you, Thomas.
Thank you very much, Gabe. Today, we're excited to announce that Agent Space is integrated with your Chrome browser to allow users to search and access your enterprise data directly from the search box in Chrome. Employees can use Agent Space to access Google-built expert AI agents, including NotebookLM, an AI-powered note-taking and research agent that allows users to upload up to 50 documents with 25 million words and then query them using AI, effectively turning notes and sources into a virtual research assistant. You can also use our idea generation agent, which accelerates innovation, brainstorming, and problem-solving. It uses a tournament-style framework to rank ideas based on employee-defined criteria, refine them, and generate new ones. Our enterprise deep research agent, which Gabe just showed you, researches complex topics on your behalf and provides you with findings in a comprehensive, easy-to-read report.
Customers and partners around the world are already using Agent Space. KPMG is building Google AI into their newly formed KPMG law firm and implementing Agent Space to enhance their own workplace operations. Cohesity is integrating with Agent Space to provide employees with greater data discovery for better decision-making while also increasing security and threat protection. Gordon Food Service is simplifying insight discovery and recommending next steps. Rubrik is leveraging agents to develop deeper customer insights and prepare for impactful sales interaction. Agent Space will provide Wells Fargo Bank the unique opportunity to modernize and simplify banking. We're now going to dive deep into five categories of agents where we're already seeing tremendous business impact. Please welcome Lisa O'Malley.
Thanks, Thomas. Let's start with customer agents. They can synthesize and reason across all types of multimodal information, including text, audio, images, and video, communicate and engage naturally with human-like speech and dialogue, connect across the enterprise applications, and take actions on behalf of the user, and be used in the contact center and on the web, on devices, in stores, in cars, and more. Customer agents built with Vertex AI Search are helping customers to quickly find answers and the right products using both text and images in search queries. Let's hear from Reddit Chief Product Officer Pali Bhat .
At Reddit, our mission is to empower communities and make their knowledge accessible to all. We've been working on this mission for nearly 20 years, which in turn has made Reddit one of the Internet's largest sources of authentic conversations. With that vast amount of conversations and perspectives, we wanted to build a unique search product that's powered with AI but still grounded in all of the real conversations and perspectives that are available on Reddit. This is why we introduced Reddit Answers, a new AI-powered way to get information, recommendations, and discussions on virtually any topic. It provides powerful AI that's grounded in Redditors' existing posts and conversations. It shows you more of what real humans think versus creating unverifiable perspectives on its own. Reddit Answers is different from any other generative AI product on the market.
It leverages Vertex AI Search to make finding the answers and perspectives people seek faster and more relevant. We've seen awesome results so far because the users who have been able to access this product and test it out really love the experience. This gets them to the heart of the conversations that they were looking for right away. That's the magic of Reddit Answers. It combines AI with the power of Reddit.
Thank you, Pali. We've also introduced Vertex AI Search for health care and retail, making it super easy for doctors, nurses, and providers to rapidly search and analyze patient data, including X-rays, scans, images, and medical histories. Retailers can add product discovery to their websites powered by Google Search. This helps them deliver hyper-relevant results and personalized recommendations for each customer, boosting conversion rates and maximizing revenue per shopper. We're seeing huge momentum for Vertex AI Search with billions of daily queries executed by our customers. For example, Lowe's is revolutionizing product discovery with Vertex AI Search to generate dynamic product recommendations and address customers' complex queries. Globo created a recommendations experience inside its streaming platform that more than doubled click-through play. Let's hear how Mercado Libre is transforming how customers discover products that they love.
Mercado Libre, Latin America's e-commerce leader, has deployed Vertex AI Search across 150 million items in three pilot countries. This multimodal search technology understands deep meaning across text and images, not just keywords. It is helping their 100 million customers find the products they love faster, already delivering millions of dollars in incremental revenue. Mercado Libre is delivering a new way to shop.
Google Cloud's own purpose-built Customer Engagement Suite is transforming customer service. Grounded in your company's data, it provides out-of-the-box functionality to build agents and works across web, mobile, call center, in-store, and with third-party telephony and CRM systems. These unique capabilities have led to rapid growth with an increase in conversational AI agent usage. DBS, a leading Asian financial services group, is reducing customer call handling times by 20%. Loveholidays saved 20% of their customer service cost per year. Our very own YouTube achieved a 75% reduction in calls abandoned while waiting to speak to a representative. Now, let's hear how Verizon is improving their customer experience using AI agents.
Verizon is transforming how they serve over 115 million connections with Google Cloud's Customer Engagement Suite. Their personal research assistant uses AI to provide 28,000 care representatives with instant, personalized information about a customer's unique needs, leading to faster and more satisfying resolutions for even the most complex inquiries. With Customer Engagement Suite, Verizon is elevating its service experience, reducing wait times, and delivering exceptional support at massive scale. Verizon developed a new way to personalize customer service.
The business impact that Verizon experienced is nothing short of extraordinary. Today, we're announcing our next generation of Customer Engagement Suite, which will include human-like voices, comprehension, and the ability to understand emotions so agents can adapt better during the conversation, streaming video support so virtual agents can respond, can interpret and respond to what they see in real- time through customer devices, AI assistants to build custom agents in a no-code interface, and the ability to use a variety of tools through API calls to interact and perform specific tasks for your application, like look up products, add to cart, or checkout, and integration with data sources, CRM systems, and popular business messaging platforms. Now, let's see a demo of all this cool stuff in action. Welcome my teammate, Patrick Marlow , to the stage.
All right. Thanks, Lisa. Hey, everyone. I'm Patrick Marlow , a product manager here at Google Cloud. I am stoked to be here today showcasing our next generation Customer Engagement Suite in action. To be honest, I'm even more excited to spruce up our keynote stage. I was thinking some greenery and flowers might be nice. You know, I've already made a couple of trips to the hardware store this morning, and I still forgot to pick up potting soil. Classic. Let's see how a next-gen agent can hopefully help me get this last order correct. We're going to start a brand new voice interaction with our agent here.
Hi there. Welcome to Simple Home and Garden . Is this Patrick?
Hey, yeah, this is Patrick. Good morning. How are you?
Good morning to you too, Patrick. I'm doing great. Thanks for asking. It looks like you've been shopping with us recently. I see you have a few things in your cart already. What can I help you with today?
Yeah, so I just bought some plants, and I'm trying to pick out potting soil and fertilizer. I'm not sure if I'm getting the right stuff. Could you help me with that?
I can definitely help with that, Patrick. To give you the best recommendations, could you show me the plants you bought? I can take a look and help you choose the best soil and fertilizer. I'm sending a video request to your browser now. Great. I can see you. Just hold the plants up to the camera so I can help identify them.
Yeah, so I have about 40 of these in various different colors.
Those are beautiful petunias. They're a great choice for vibrant color. Let me take a closer look at the items in your cart. OK, I see you have standard potting soil and general-purpose fertilizer. That could work. Petunias really thrive in a rich, well-draining soil and a fertilizer specifically for flowering plants. OK, I've found some recommendations for your petunias.
Yeah, I'm taking a look at these now. They look fantastic. Thanks.
Great. Would you like me to remove the standard potting soil and general-purpose fertilizer and add the Bloom Booster Potting Mix and Flower Power Fertilizer to your cart?
Yeah, let's go ahead and do that.
OK, I've updated your cart. Is there anything else I can help you with today?
I mean, not unless you can come over and plant these for me.
Funny you should mention that. We actually do offer professional landscaping services. Would you be interested in a quote?
Yeah, I mean, how much would something like that cost?
For planting 40 petunias, I would suggest a four-hour appointment, which would come out to $200.
OK, that's interesting. I'm curious, do you also price match?
Yes, we do price match on occasion. It is usually on a case-by-case basis.
Oh, in that case, I most definitely saw an ad from one of your competitors, Greenscapes, where they were offering 50% off first-time landscaping services for new customers. You should totally give me that 50% discount.
Apologies. It looks like that amount is beyond what I'm authorized to approve. Let me check with my supervisor to see what we can do. Just a moment.
I'm going to step away from being the human user in this conversation for a moment. We're going to go behind the scenes over here to our call center. What you're going to see here in our CRM Salesforce is that our virtual assistant, our virtual agent, has escalated up to a human call center manager, also played by me. What I can do here is guide the agent through this portion of the conversation without fully taking over the conversation. You can see here, Patrick is requesting a price match for a 50% off offer. I'll say something like, you know, we can't do that, but we can do 20%. Oh, let's say we can do 20% instead. I'm going to send this message, and then we're going to pick up the conversation on the other side.
Good news, Patrick. My supervisor has approved a discount. We can offer you 20% off our landscaping services. I've applied a 20% discount to the landscaping services.
Oh, that's awesome. I'll take it.
Fantastic. Let's get that scheduled. I can have someone out tomorrow from 8:00 A.M.- 12:00 P.M. or between 1:00 P.M. and 5:00 P.M. Which would you prefer?
Let's definitely do the afternoon time because I have a pickleball tournament in the morning.
Great. You're all set. You'll receive a confirmation email in just a moment with all the details. Is there anything else I can assist you with today, Patrick?
Yeah, do I actually have to pay for the landscaping services right now?
No, we'll just add this to your account. You can pay once the service is complete. Anything else?
No, I'm just going to finish checking out here. You've been really wonderful today. Thanks for your help.
You're very welcome. Thanks for choosing Simple Home and Garden. Have a great day and good luck at your pickleball tournament.
Now, that was pretty amazing, right? That entire thing was 100% real and live. All of the tools needed to build experiences just like that are available for you to start using today. Thanks, everyone. Back to you, Lisa.
Pretty amazing. We're also helping to improve conversational customer experiences beyond the call center by offering purpose-built agents that address specific industry use cases, including food ordering, automotive, and retail. For example, Wendy's AI drive-thru ordering system handles 60,000 orders daily. Mercedes-Benz provides conversational search and navigation in the new CLA series. The Home Depot has built Magic Apron, an agent that offers expert home improvement guidance 24/7. We have tremendous partnerships. For example, ServiceNow CRM works with Customer Engagement Suite, helping to automate and personalize customer interactions across systems. Now, let's talk about creative agents that are being used to superpower creative teams, including those in media production, marketing, advertising, design, and more. In some cases, agents are augmenting creative teams to enable content production at massive scale. In others, they're helping reimagine how stories can be told for a new generation of audiences.
One of the most amazing examples is the enriching of The Wizard of Oz at the Las Vegas Sphere and how Veo 2 helped to bring it to life. Let's hear from CEO of Sphere, Jim Dolan, and the visionaries who made it happen.
Sphere is an experiential medium. We looked for content that would accentuate all of the different capabilities inside of the venue. That was our criteria for choosing The Wizard of Oz.
We knew that it was really hard to tackle using traditional means. It is possible to do it with AI.
We ultimately came to the conclusion that Google was the only company that was actually capable of doing this.
Alongside Google's DeepMind researchers, we trained AI models so that when you see Dorothy dancing, you see her full body dancing down to her ruby slippers. For Google to bring Veo 2, we were really excited because that infrastructure that exists and that compute power was needed to do everything we're doing. Sphere Studios has partnered with Google Cloud, and we've successfully deployed finishing technology in Google's cloud infrastructure. Turnaround times, transmission times, all of the things that sometimes can slow a traditional studio down, now we're able to do them a lot faster and with a lot more impact using Google Cloud.
My hope for it is that we keep exploring different ways to create this kind of content and to take great performances from the past and bring them to life today. I think the world is going to be amazed.
Beyond entertainment, AI is helping creative agencies revolutionize marketing for their clients. WPP built Open as a platform powered by Google models that all of its employees worldwide can use to concept, produce, and measure campaigns. Monks.Flow is using Google AI to help localize creative for campaigns. The Brandtech Group built Pencil, a generative AI platform for brands to create ads, like this recent mockup for Japan Airlines. Customers are increasing marketing performance and reducing production time with creative agents. Mondelēz quickly generates visuals for global brands like Oreo and Cadbury. Bloomberg Connects is making museums more accessible. We are absolutely thrilled to partner with Adobe, the leader in creativity, to bring our advanced Imagen 3 and Veo 2 models to applications like Adobe Express. Now, please welcome Brad Calder to the stage to talk about data agents.
Thanks, Lisa. Data agents know what data to utilize and what questions to ask. They enable data teams to effectively manage data and business teams to activate it. Mattel is an iconic brand, making toys from Barbies to Hot Wheels. Let's hear from Mattel CEO, Ynon Kreiz , on how they harness their data with Gemini.
At Mattel, our mission is to create innovative products and experiences that inspire fans, entertain audiences, and develop children through play. This year, we're celebrating 80 years. While we first made our mark as a toy company, Mattel today is a global brand management company home to one of the most iconic portfolios in the world. Our partnership with Google Cloud has helped us synthesize millions of points of consumer feedback, from phone calls and emails to online reviews and social media comments, delivering insights and opportunities to deepen our relationship with Mattel fans. Before partnering with Google Cloud, teams identified patterns manually. Now, we can analyze sentiment and consumer preferences in real- time. We can instantly identify key issues and trends, improving both efficiency and innovation.
For example, we improved the ride mechanism in the Barbie DreamHouse elevator and enhanced the interactive features in the Fisher-Price Kick & Play Piano Gym . These are two of our top-selling global products that have been made even better through data-driven insights. We see Google Cloud as a true partner in bringing the magic of play to life for every Mattel fan.
Thanks, Ynon. My kids love playing with Fisher- Price Gym. Our data platform, BigQuery, has 5x more customers than the two leading independent data cloud companies. With BigQuery, you can activate all your data for AI, combining structured and unstructured data, such as tables, text, logs, images, and video. You can also work with open formats like Apache Iceberg, directly integrated into BigQuery. You can use BigQuery to access data in any storage system or in any SaaS application on any cloud. Multimodal analysis with Gemini and BigQuery has grown more than 16x this past year. Now, if you're a big Oracle customer, the full range of Oracle database services running on OCI are integrated with BigQuery, Gemini, and Vertex AI. They're being deployed natively in 20 Google Cloud locations, serving customers such as Macy's and Sabre.
Today, we're very excited to announce specialized agents for every member of your data team. Now, for data engineering teams, we deliver agents for all aspects of a data engineering lifecycle, from catalog automation to metadata generation to maintaining data quality to data pipeline generation. For data science teams, our AI agent acts as a comprehensive coding partner in your data science notebook, accelerating every step of your workflow from data loading and feature engineering to predictive modeling. For data analysts and business users, our conversational analytics agent performs powerful, trustworthy analysis entirely in natural language. You can also embed this agent in line in your own web or mobile application. For over a decade, Spotify has partnered with Google Cloud to cost-effectively handle massive scale.
They use BigQuery to harness enormous amounts of data to deliver personalized experiences to over 675 million users worldwide, including many of us here. Unilever uses BigQuery to reach millions of retailers in emerging markets. Bayer built an agent that predicts flu trends. Now, customers are also taking advantage of our databases with AI. For example, Nuro, an autonomous driving company, uses AlloyDB to identify challenging scenarios on the road. Public sector organizations like State of Nevada are using agents to speed up benefit claims. Let's find out more.
The Nevada Department of Employment, Training, and Rehabilitation provides critical unemployment and job placement services. To support limited staff in a regulated space, Nevada DETR developed an appeals AI assistant powered by BigQuery and Vertex AI. It synthesizes case data to help appeals referees make fair approvals 4x faster, surpassing DOJ standards. Nevada Department of Employment, Training, and Rehabilitation is creating a new way to serve constituents.
Now, let's see all of this in action. Please welcome Yasmeen Ahmad.
Thank you, Brad. I'm here to show you the future of data science made easy. All it takes is BigQuery Colab and Vertex AI, now powered with Gemini. Say you're running a consumer goods company. Sales are booming, but cash flow is slowing down. Why? To answer this question, we need to see everything from sales to invoices to customer signal. Let's take a look at our data. Traditionally, data is siloed. Now, BigQuery helps me connect everything, including SAP deep integration and real-time feeds from Salesforce and even Google Ads. See? Easy. Let's ask our data engineering agent to now do the heavy lift. I'm going to add my first prompt from the clipboard. To do this cash flow analysis, we're going to combine invoices, sales, and audience data from all of these sources into a single multimodal data table.
Instantly, we have a unified view of everything, no complex integrations and no waiting. Easy. Of course, our new table is a little messy. Look at those dates. It is a good thing now with BigQuery, we have access to Gemini-powered recommendations. Look at that, a clean data set. Super easy. Let's now move to BigQuery Data Canvas to do some analysis. Here, we can see our structured data is ready to go. However, to do a true cash flow analysis, I need to extract signals from my PDF invoices. Not so easy. Here, I can ask our data science agent to help me extract buyer and payment information and group buyers into segments. In the past, this would have taken hours of manual effort. Definitely not easy. Now, with BigQuery's new AI query engine, without having to review each PDF, I can automatically extract key information.
We can group buyers into segments using Gemini's real-world knowledge. Again, super easy. What exactly is causing our cash flow drop from January to March? Here, our data science agent uses Gemini's new thinking model and BigQuery machine learning to build an automated data science workflow right before our eyes. It's analyzing hundreds of dimensions in mere seconds. It looks like we have our answer, payment terms. It looks like our new 36-month payment promotion offer, while boosting sales, has caused the recent cash flow dip. I wonder how this is impacting my cash forecast. To do this, I want to jump to code. I'm going to extract my analysis here into a BigQuery notebook. In our notebook, we can ask our data science agent to, again, help us write some code.
Here, we'll ask our agent to build a forecast for the next three months, broken down by buyer category. BigQuery now uses Google's new pre-trained time series forecasting model to build this out. We can reveal the big insight. It looks like wholesalers taking those long 36-month payment terms are causing the issue. Finding this answer? Easy. We can make this analysis even more powerful. We can ask our data science agent to include product category as a breakdown. BigQuery Colab composer instantly gets to work updating all of our code. As we see forecasts now, including buyer segment and product category, we can answer a huge range of potential questions. So easy. In fact, it looks like our 36-month terms are impacting fast-moving segments like food and beverage and not other segments, for example, medication. This insight allows for surgical precision.
Instead of a blunt action like removing the 36-month promo offer entirely, we can make a data-driven, targeted, easy decision. Pretty incredible, right? This whole process used to take months of manual work, but today, it took just a few minutes. Gemini and Vertex AI have made BigQuery a complete data science platform, unlocking new insights faster than ever with both natural language and code. That, my friends, is the future of data science made, say it with me, easy. Back to you, Brad.
Thanks, Yasmeen. That was amazing. Now, just like with data, Gemini's fast performance, large context window, and reasoning make it highly effective for coding agents. We offer Gemini Code Assist in Google Cloud, Android Studio, Firebase Studio, and your favorite IDE. Our enterprise version understands your code-based standards and conventions. Companies like Ampere from Renault Group, Broadcom, CME Group, PayPal, and Wipro use Code Assist today. Today, we're announcing new Code Assist agents to help with everything from modernizing code to helping with the full software development lifecycle. Developers can interact with our agents on a Kanban board, which provides a real-time display of the tasks Code Assist is working on, as well as the ability for developers to interact with our agents. Code Assist also has integrations with dozens of partners, such as Atlassian, Sentry, Snyk, and many more coming soon.
Now, outside of Google, Gemini is also available for your development needs in Aider, Cursor, GitHub Copilot, Replit, Tabnine, and Windsurf. If you want to see more, join me tomorrow at the developer keynote to see Code Assist in action. Now, to share what's new in security, please welcome Sandra Joyce.
Thanks, Brad. Security agents can dramatically increase the speed and effectiveness of security analysts. The integration of AI across our security products is just one reason why organizations around the world are making Google part of their security team. We offer critical cyber defense capabilities in today's challenging threat environment, such as threat intelligence drawn from Mandiant investigations, Google Operations, VirusTotal, and more. You know who's targeting you and where you're exposed. A comprehensive security operations platform that applies our intelligence for proactive threat detection, investigation, and response anywhere you operate. Cloud security and risk management that uses virtual red teaming to find risks that other solutions can't, protecting your workloads and AI across all your clouds. Mandiant services provide expertise before, during, and after security incidents. Today, we're introducing new security agents that analyze malware and triage alerts to speed up investigations.
Our capabilities have been adopted by thousands of organizations, like Charles Schwab, who uses Google SecOps to stay proactive in responding to cyber threats. They've gained new visibility across their entire environment while reducing investigation and resolution time. Vertiv, who are detecting more events and closing investigations faster with Google SecOps. Dun & Bradstreet , who are using Security Command Center to centralize monitoring of AI security threats. Vodafone, who use Vertex AI along with open-source tools and Google Cloud Security Foundation to establish an AI security governance layer. Finally, the Government of Singapore, who uses Google Cloud Web Risk to protect their residents online. These organizations and many more benefit from our individual products and services. We can drive even better outcomes from converging our security capabilities. For that, we're introducing Google Unified Security.
Google Unified Security brings together unmatched visibility, faster threat detection, AI-powered security operations, continuous virtual red teaming, the most trusted browser, and Mandiant expertise in one converged security solution running on a planet-scale data fabric. For our last demo, let's see how this works with Payal Chakravarty and Nav Jagpal.
Hi, everyone. I'm Nav, and I'm a developer building a cool new app using Vertex AI.
I'm Payal, a security analyst. Often juggling multiple security tools and manual processes, I'm here to show you how Google Unified Security, or GUS for short, can proactively protect your applications no matter where you're building them. Nav, what have you been up to?
I was trying to test this app, and let's just keep this between us. I might have made a few mistakes along the way.
Go on.
To speed up development, I installed a Chrome extension, which helps me test my prompts across multiple public LLMs. You know, I didn't think anything of it at the time.
Let's see what's going on here. Nav, while you were doing this, which is a legitimate action and Chrome extension, there may have been a potential data leak. As you see here in the centralized risk dashboard that prioritizes risk across all my company's assets and activities, GUS detected that you were copying and pasting sensitive data into the public LLM models. If I click here further, Gemini's agentic AI has automatically triaged this alert, confirmed the data leak with high confidence, and taken an automated response to quarantine that specific Chrome extension immediately. Wow, this would have taken me days to figure out in other tools.
Wait, so GUS detected what I was doing and stopped it automatically? I mean, why is it even a big deal that I was testing my prompts like this in the first place?
Because those prompts could contain confidential company data. GUS protected not only you, but mitigated insider risk by updating Chrome policy for the entire organization. Now that I look at it, the agent has picked up on a few other correlated risks. Is there anything else you want to tell me about, Nav?
Oh, you know what? Come to think of it, I wanted to test my application, so I spun up a VM. You know, I just wanted to get things working really quickly, so I might have been a little bit lax with those firewall settings.
There is something interesting going on with that VM. GUS detected malicious traffic to that VM and automatically associated that with an emerging threat actor that the Google Threat Intel team has been tracking.
Wait, hold up. You're saying that while I was testing my app for just a few hours, somebody was trying to break into it?
Exactly. In the world of security, a few hours could be a lifetime, Nav. GUS recognized the risk in real- time and took action.
That's wild. Is there anything else that GUS thinks I should be doing to protect my application?
Yeah. The agent here recommends that we harden your AI model with Model Armor, its new AI protection capabilities. You will see here, at the click of a button, it will take a minute here. At the click of this button, you will see that Model Armor starts analyzing inputs in real- time, in line, blocking malicious inputs before they reach the model.
OK. GUS is able to detect all risks in one place, connect the dots, and take action? You know, as a developer, it really gives me peace of mind knowing that GUS has my back at all times.
Yes, Nav. GUS not only has your back on this environment in Google Cloud, GUS is an integrated open platform that can protect any environment, any data, from endpoint, firewall, networks, identity, really any cloud, any model. Further, for added protection, we have access to GUS's expertise in incident response and threat hunting around the clock.
I'm super excited that Google is a part of our security team. Thank you, everyone. Back to you, Thomas, to take us home.
Thank you both. We are continuing to invest in our security offerings. Just last month, we signed a definitive agreement to acquire Wiz, a leading multi-cloud security platform to provide better cybersecurity alternatives for businesses and governments around the world. As you have heard throughout this keynote, we are delivering an amazing stream of new innovations and making it easy to integrate those innovations into your existing technology landscape. We do this in four important ways. First, connecting your clouds with other clouds and applications, enabling secure cross-cloud networking with Cross-Cloud Interconnect, using your existing security platforms, applying federated identity with Microsoft Entra ID, and using BigQuery and AlloyDB without moving from Amazon or Azure, which is helping companies like Johnson & Johnson and Walmart. Second, we are working with many leading ISVs to integrate them with Google AI.
You have access to these ISV solutions, which are pre-integrated and easily deployed from the Google Cloud Marketplace. Third, our services partners have created thousands of agents that bring their deep understanding of your industry and existing IT systems. In fact, Accenture, Capgemini, Deloitte, HCLTech , KPMG, TCS, and Wipro are all making agent announcements with Google Cloud today. Fourth, we're enabling sovereign clouds with partners to meet international regulations. Today, we offer Google Cloud Sovereign AI services in our public cloud, sovereign cloud, and distributed cloud, as well as with Google Workspace. Now, just in closing, what an amazing time for all of us to experience and work with these technology advances.
We at Google Cloud are committed to helping each of you innovate by delivering the leading enterprise-ready AI-optimized platform with the best infrastructure, leading models, tools, and agents, by offering an open multi-cloud platform and building for interoperability so we can speed up time to value from your AI investments. We are honored to be building this new way to cloud with each of you. To everyone here and all of those watching online, thank you so much for joining us for Google Cloud Next. We hope to see you again in 2026. We'll be back here in Las Vegas, April 22.