Build more capable and reliable AI systems by combining context-aware retrieval-augmented generation (RAG) with agentic decision-making in an enterprise AI platform, all in Java! This session covers everything from architecture, context construction, and model routing to action planning, dynamic retrieval, and recursive reasoning, as well as the implementation of essential guardrails and monitoring systems for safe deployments. Learn about best practices, trade-offs, performance, and advanced techniques like evaluations and model context protocol.

Organizations are facing sophisticated and growing cyberthreats from commercially driven ransomware groups and state-sponsored adversaries that legacy productivity solutions struggle to defend against. Learn how Google’s multilayered approach – AI threat defenses, a reduced attack surface, and built-in security controls in Google Workspace, Chrome Enterprise, and ChromeOS – can effectively combat the most prevalent cyberthreats and block malicious actors from gaining access to your data and disrupting your business.

Audiences around the world have almost limitless access to content that’s only a click, swipe, or voice command away. Companies are embracing cloud capabilities to evolve from traditional media companies into media-tech and media-AI companies. Join us to discover how the cloud is maximizing personalization and monetization to enable the next generation of AI-powered streaming experiences for audiences everywhere.

This session dives into the latest advancements in securing and managing your Cloud Run workloads at enterprise scale. Join us to learn about new features and techniques to meet the highest security standards, strategies for managing large-scale deployments, and solutions to common issues like IP exhaustion. Plus, one of our customers will share their firsthand experience managing a massive fleet of Cloud Run workloads.

Get the inside story of Yahoo’s data lake transformation. As a Hadoop pioneer, Yahoo’s move to Google Cloud is a significant shift in data strategy. Explore the business drivers behind this transformation, technical hurdles encountered, and strategic partnership with Google Cloud that enabled a seamless migration. We’ll uncover key lessons, best practices for data lake modernization, and how Yahoo is using BigQuery, Dataproc, Pub/Sub, and other services to drive business value, enhance operational efficiency, and fuel their AI initiatives.

In this session, we’ll explore Google’s latest developments in Google Kubernetes Engine (GKE) that enable unprecedented scale and performance for AI workloads. We’ll dive into how Anthropic leverages these capabilities to manage mega-scale Kubernetes clusters, orchestrate diverse workloads, and achieve breakthrough efficiency optimizations.

In this session, we’ll explore how you can manage human and nonhuman identities on Google Cloud. We’ll discuss how these identities are defined, managed, and used to secure access to resources, and we’ll cover topics such as cryptographic managed workload identities, identity federation, and flexible identity onboarding options on Google Cloud.

Generative AI agents have emerged as the leading architecture for implementing complex application functionality. Tools are the way that agents access the data and systems they need. But building and deploying tools at scale brings new challenges. Learn how MCP Toolbox for Databases, an open source server for gen AI tool management, enables platforms like LangGraph and Vertex AI to easily connect to enterprise databases.

Join us for an interactive session where we’ll build, deploy, and scale inference apps. Imagine creating and launching generative AI apps that deliver personalized recommendations and stunning images, all with the unparalleled efficiency and scalability of serverless computing. You’ll learn how to build gen AI apps effortlessly using Gemini Code Assist; deploy gen AI apps in minutes on Cloud Run, using Vertex AI or on-demand, scale-to-zero serverless GPUs; and optimize the performance and cost of AI workloads by implementing best practices.

Learn how to evaluate and optimize the impact of AI-assisted software development with Gemini Code Assist. This session covers processes for measuring AI-assistance effectiveness, exploring quantitative and qualitative measures available with Gemini Code Assist, and integrating with Cloud Monitoring and Cloud Logging. Discover how to leverage DevOps Research and Assessment (DORA) metrics to track productivity gains. Whether you’re a developer, team lead, architect, or IT manager, you’ll gain insights into measuring the impact of AI assistance.

AI-enabled browser agents are in the news now, but it’s not always clear how they solve real-world problems. In this session, we’ll share our experience building a web browser agent by integrating Gemini into an end-to-end service that follows text instructions to take actions in a web application. We’ll take you through our journey of creating the agent, share the research that inspired us, and show how we’ve used the system to tackle practical problems like validating user flows in the UI and semantically checking web links.

Imagine starting your workday with AI agents at your fingertips, from right within your browser. Join us in this session to learn how Google Agentspace, seamlessly integrated with Chrome and NotebookLM, can change the way you approach work. Think of automating your personal workflows, accessing critical information instantly, and working in unison with AI – all within your familiar browser environment.

Is your platform ready for the scale of rapidly evolving models and agents? In this session, we’ll explore strategies for scaling your cloud native AI platform - empowering teams to leverage an increasing variety of AI models and agent frameworks. We’ll dive into tools and practices for maintaining control and cost efficiency while enabling AI engineering teams to quickly iterate on Google Kubernetes Engine (GKE). We’ll explore how NVIDIA NIM microservices deliver optimized inference with minimal tuning. 

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

According to Andreessen Horowitz, 93% of Fortune 500 companies surveyed currently use three or more AI model providers, and now AI agents will proliferate and become standard. With the massive shift in enterprise AI adoption and the pace of change, enterprises need to modernize their network and security to unlock the value that AI generates and keep pace with rapid changes. Learn how to make your network and security AI-ready, plus discover new innovations to reduce infrastructure costs, improve user experience, enable faster developer velocity, and protect your AI infrastructure from new security threats.

This talk demonstrates a fashion app that leverages the power of AlloyDB, Google Cloud’s fully managed PostgreSQL-compatible database, to provide users with intelligent recommendations for matching outfits. User-uploaded data of their clothes triggers a styling insight on how to pair the outfit with matching real-time fashion advice. This is enabled through an intuitive contextual search (vector search) powered by AlloyDB and Google’s ScaNN index to deliver faster vector search results, low-latency querying, and response times. While we’re at it, we’ll showcase the power of the AlloyDB columnar engine on joins required by the application to generate style recommendations. To complete the experience, we’ll engage the Vertex AI Gemini API package from Spring and LangChain4j integrations for generative recommendations and a visual representation of the personalized style. This entire application is built on a Java Spring Boot framework and deployed serverlessly on Cloud Run, ensuring scalability and cost efficiency. This talk explores how these technologies work together to create a dynamic and engaging fashion experience.

Join Woosuk Kwon, Founder of vLLM, Robert Shaw, Director of Engineering at Red Hat, and Brittany Rockwell, Product Manager for vLLM on TPU, to learn about how vLLM is helping Google Cloud customers serve state-of-the-art models with high performance and ease of use across TPUs and GPUs.

Ever wondered what your work interface with AI agents will look like? Join us to learn about the latest advancements in Google Agentspace – your launch point for enterprise-ready AI agents. In this session, we’ll cover the exciting new capabilities and ready-to-use agents in Agentspace, and the new use cases enabled by it.

Learn how LG AI Research uses Google Cloud AI Hypercomputer to build their EXAONE family of LLMs and innovative Agentic AI experiences based the models. EXAONE 3.5, class of bilingual models that can learn and understand both Korean and English, recorded world-class performance in Korean. The collaboration between LG AI Research and Google Cloud enabled LG to significantly enhance model performance, reduce inference time, and improve resource efficiency through Google Cloud's easy-to-use scalable infrastructure

Maximize the efficiency of your machine learning workloads on Google Cloud infrastructure. This session delivers actionable strategies for in-depth diagnostics on both TPUs and GPUs. Learn to visualize model architectures, analyze critical performance metrics, and pinpoint optimization opportunities. Empower your data-driven decision-making and achieve significant performance gains through practical diagnostic techniques.

Ready to advance your career in the cloud? This meetup is for anyone interested in earning a Google Cloud certification or adding to their certification portfolio. Get expert advice from certified professionals, connect with fellow learners, and discover the right certification path for you. Leave with helpful study tips and maybe even a few study partners!

Discover how leading manufacturing companies are leveraging AI to transform employee experience and drive productivity with AI-enabled workflows and assistants. Learn about the evolution of these tools, the positive user feedback they received, and further possibilities around image and code generation. This session will provide a compelling look at how AI can revolutionize large enterprises, with practical insights into implementation and future possibilities.

This session provides a Google thought-leadership perspective on the importance of product-led growth for all organizations and how it can complement and accelerate sales-driven strategies. We’ll explain how we’ve scaled software-as-a-service (SaaS) product-led growth principles to Google Cloud, and we’ll illustrate how Google Cloud can be the ideal partner for creating, analyzing, and optimizing product-led growth efforts to drive incremental revenue without increasing sales head count.

Learn how to leverage Google Cloud's cutting-edge AI models to rapidly develop solutions for critical healthcare challenges. Gain practical skills and empower your startup to revolutionize diagnostics, drug discovery, and personalized treatment. This session provides the skills and confidence to build impactful AI solutions and tackle real-world biotech challenges.

Cross-Cloud Network, built on Google’s planet-scale network, has transformed how organizations connect and secure workloads, users, and data across hybrid and multicloud networks. It simplifies complexity, strengthens security, and helps deliver faster business outcomes. Join this session to learn about new innovations in 2025 with the Cross-Cloud Network that allow you to secure and optimize AI and machine learning (ML) workloads, connect global enterprises, expand network security to cover all threat vectors as you connect distributed multicloud apps, and deliver web and media workloads.

Unleash the power of AI-driven analytics with Gemini and BigQuery. Learn how to uncover trends, automate complex queries, and make smarter decisions. Explore real-world examples from industry leaders using AI to extract insights from unstructured data like text, images, and audio to streamline operations and unlock growth.