Author: Mayank Juneja
Detecting the Unexpected: Built-in Real-Time Anomaly Detection With Confluent Cloud for Apache Flink®
Learn how the built-in anomaly detection ML function in Confluent Cloud for Apache Flink® enables event-driven AI agents to detect and act on outlier system events faster.
Faster, Smarter, More Context-Aware: What’s New in Streaming Agents
Explore new Streaming Agents features — Agent Definition, Observability & Debugging, and access to Real-Time Context Engine — to build intelligent, context-aware AI on Confluent.
Unleash Real-Time Agentic AI: Introducing Streaming Agents on Confluent Cloud
Build event-driven agents on Apache Flink® with Streaming Agents on Confluent Cloud—fresh context, MCP tool calling, real-time embeddings, and enterprise governance.
Event-Driven AI Agents: Why Flink Agents Are the Future of Enterprise AI
Explore how Flink Agents redefine enterprise AI with real-time data, event-driven processing, and scalable autonomy—built for the future of AI workflows.
Introducing Real-Time Embeddings: Any Model, Any Vector Database—No Code Needed
Confluent’s Create Embeddings Action for Flink helps you generate vector embeddings from real-time data to create a live semantic layer for your AI workflows.
Let Flink Cook: Mastering Real-Time Retrieval-Augmented Generation (RAG) with Flink
With AI model inference in Flink SQL, Confluent allows you to simplify the development and deployment of RAG-enabled GenAI applications by providing a unified platform for both data processing and AI tasks. Learn how you can use it to build a RAG-enabled Q&A chatbot using real-time airline data.