RAG for PDFs That Doesn’t Fall Apart on 100+ Pages
In DocuChat, we built a PDF pipeline: document → chunks → embeddings → vector database → context for the LLM. The user uploads a file and chats with it like in a messenger.
In DocuChat, we built a PDF pipeline: document → chunks → embeddings → vector database → context for the LLM. The user just uploads a file and chats with it like in a messenger — no need to play the “where was this on page 78?” game.
The main challenge is large documents. If you feed an LLM a 100+ page contract in one go, it quickly slips into “I think I got it” mode. That’s why we built chunking + retrieval: the model gets only the relevant pieces, but doesn’t lose the document’s overall logic.
We also added legal review through chat: edits are shown as diff suggestions, while preserving layout, tables, and numbering. In other words, it’s not “the smart editor rewrote everything from scratch,” but careful changes that you wouldn’t be embarrassed to show a lawyer.
With the wave of AI assistants in 2025, this is no longer a feature — it’s a must-have for docs where you can’t afford to mess up.