Standalone RAG Agent (Beta)

The RAG Agent enhances our Integration Hub by connecting AI language models with our enterprise knowledge systems through retrieval-augmented generation. When a query arrives (from a chatbot, portal, or application), the agent:

1. Performs semantic search across vector databases populated by Micro-Integrations
2. Retrieves relevant enterprise data and context
3. Sends this context along with the query to a configured LLM
4. Returns a grounded, accurate response via the event mesh

This real-time system ensures users receive up-to-date information, improves customer satisfaction with faster answers, and allows support teams to focus on complex cases requiring human expertise. The agent’s event-driven design enables multiple systems to access AI capabilities without creating new silos.

Built for enterprise demands, it handles concurrent queries with the lowest latency possible, manages back-pressure during load spikes, and provides error logs across the RAG workflow for monitoring.