Show HN: LangChain and Tensorlake = Better Document RAG

We built this at Tensorlake after struggling with brittle prompt-based extractors. This system lets you parse unstructured docs and extract contextual information quickly with a LangGraph Agent.

I’d love thoughts from others building RAG apps, especially around field accuracy and chunking strategies. What would you improve?