Relying on third-party-hosted artificial intelligence (AI) models may not always be an option for your application. You are also not guaranteed support for those model endpoints through your next software release. By hosting state-of-the-art AI models like Gemma in the same environment as AlloyDB Omni, you can run scalable generative AI apps on any cloud or on premises, for regulatory needs, with low latency. Learn from Neuropace how they run Omni for enterprise-grade vector search capabilities in their local environment, which contains sensitive customer workloads.

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Ditch legacy and embrace freedom with AlloyDB Omni, your hybrid and multicloud enterprise database. Run anywhere, from data centers to the public clouds of your choice, and unlock performance and ease of management. Elevate your apps with HTAP and built-in generative AI to build vector embeddings for lightning-fast search, remotely or locally – no connectivity needed. Simplify operations with the Kubernetes operator: automate lifecycle, HA/DR, and scale effortlessly. Learn more about AlloyDB Omni and supercharge your data strategy, anywhere.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

In this workshop, you will learn how you can easily create a Retrieval Augmented Generation (RAG) application and how to use it. We will be highlighting AlloyDB Omni (our deploy-anywhere version of AlloyDB) with pgvector's vector search capabilities. You will learn to run an LLM and embedding model locally so that you can run this application anywhere. Creating an app in a secure way with LLMs playing around your data is harder than ever. Come and build with me!

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.