Knowhere helps AI agents read documents better. Turn messy docs into clean, structured knowledge for better RAG.

👋 Hello PH!

We built Knowhere because we wanted documents to work for both humans and agents.

A lot of builders today are vibe coding AI apps, while agents like our OpenClaw need reliable, structured context to do real work. Most parsers still miss the parts that matter most, like hierarchy, tables, images, and layout.

Knowhere turns messy docs into structured, citation-ready knowledge with clean chunks and usable outputs for vector and vector-free RAG, retrieval, and downstream agent workflows.

🏗️ If you're an AI app builder trying to plug in RAG but stuck on chunking, grab an API key and try it out. We offer $5 in free credits: https://knowhereto.ai/api-keys

🦞 If you want to give an agent document parsing superpowers out of the box, you can also use our OpenClaw integration: https://knowhereto.ai/claw.

If you have any questions, feel free to reach out at team@knowhereto.ai.

Would love to hear what kinds of docs are hardest for your stack today.

@busmark_w_nika Nika, would this be interesting to you?

@stevekwok isn't it something similar to klu.so ?

@busmark_w_nika It’s more like an OpenClaw version of NotebookLM

This looks super promising 🚀
One of the biggest pain points I’ve seen with RAG pipelines is exactly this—poor chunking and loss of structure (especially tables + hierarchy). Love how you’re focusing on making docs actually usable for agents, not just humans.

Curious to know—how well does it handle highly unstructured PDFs or scanned documents?

Finally, an AI tool that doesn’t mess up my nested tables.