DeeperMind.ai helps you explore, search, and summarize your own documents using a combination of semantic search and generative AI. Ideal for personal knowledge bases, internal docs, or smart FAQ systems.

I'm the solo developer behind DeeperMind.ai. After 20+ years building software, I wanted to create a tool that finally makes document search useful — combining semantic understanding with AI-generated insights. This project started out of frustration: we have more documents than ever, but still waste time trying to find the right info. DeeperMind lets you upload your own files and get smart answers instantly — whether you're building a personal knowledge base or managing internal docs. It’s still in beta, so I’d love to hear your feedback — bugs, ideas, anything 🙌 Thanks for checking it out!

Finally cracked large-scale semantic chunking — and the answer precision is 🔥

Hey 👋

I’ve been heads down for the past several days, obsessively refining how my system handles semantic chunking at scale — and I think I’ve finally reached something solid.

This isn’t just about processing big documents anymore. It’s about making sure that the answers you get are laser-precise, even when dealing with massive unstructured data.

Here’s what I’ve achieved so far:

Clean and context-aware chunking that scales to large volumes

Smart overlap and semantic segmentation to preserve meaning

Ultra-relevant chunk retrieval in real-time

Dramatically improved answer precision — not just “good enough,” but actually impressive

It took a lot of tweaking, testing, and learning from failures. But right now, the combination of my chunking logic + OpenAI embeddings + ElasticSearch backend is producing results I’m genuinely proud of.

If you’re building anything involving RAG, long-form context, or smart search — I’d love to hear how you're tackling similar problems.

Let’s connect and compare strategies!