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Unleash cutting-edge GenAI with a data streaming platform. Build RAG use cases with real-time, contextual and trustworthy data for your LLMs, vector databases, and GenAI applications.

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A Guide to Event-Driven Design for Agents and Multi-Agent Systems

Learn how to build and scale real-time enterprise AI agents. Includes design pattterns, agentic AI use cases and architectures.

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Powering AI Agents with Real-Time Data Using Anthropic’s MCP and Confluent

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What Is Flink AI Model Inference?

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The Developer's Guide to RAG

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Real-Time AI Use Cases

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AI-Powered Supply Chain at GEP Worldwide

Hear GEP's story on using data streaming in their AI stack to help power a GenAI chatbot that provides real-time, contextualized insights for enterprise customers.

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Scaling AI Agents at Reworkd

Combining LLMs with Confluent data streaming makes it possible to scale agents that can write, test, and iterate on web scraping code.

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Live Recommendations at Whatnot

AI projects can only be successful with fresh, accurate data. Real-time streaming powers in-the-moment product recommendations for greater user engagement.

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AI Service Chatbot at Penske

Learn how Penske is using the power of data streaming and AI to drive better customer experiences, including maximizing fleet uptime for its trucking customers.

Why Confluent Data Streaming Platform

Build a real-time, contextualized, and trustworthy knowledge base for your GenAI applications. 

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Stream

Continuously capture and share real-time events with AI systems and applications.

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Connect

Integrate disparate data from any environment with 120+ pre-built and custom connectors.

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Process

Use Flink stream processing to enrich data with real-time context at query execution.

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Govern

Use data lineage, quality controls and traceability to ensure data for AI is secure and verifiable.

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