Fixing RAG's Biggest Problem — POMA AI Elevator Pitch
Most RAG systems break documents into chunks without preserving structure or context. A one-minute look at that problem — and how POMA AI's structure-aware ingestion and chunking fixes it.
Guided walkthroughs of POMA AI's context-engineering stack.
Most RAG systems break documents into chunks without preserving structure or context. A one-minute look at that problem — and how POMA AI's structure-aware ingestion and chunking fixes it.
End-to-end tour of the Grill loop: ingest documents in the POMA Console, watch them indexed into a project, then query that context from an agent over MCP.
Add POMA Grill as a connector in Claude Desktop from the connector directory, then query your indexed documents directly inside a conversation.
Live walkthrough of pairing POMA AI's PrimeCut ingestion and chunking with your own Qdrant instance — from documents to structure-aware retrieval, with a runnable notebook to follow along.
The current notebook was updated and can slightly differ from the one in the video.