Neural Search Engine
Semantic search for unstructured documents
Projects
Selected work and code.
Neural Search Engine
Semantic search for unstructured documents
50% faster document discovery in pilot deployments
A search engine that understands meaning, not just keywords. Built for teams drowning in unstructured documents — contracts, research papers, internal wikis — where keyword search fails.
Uses transformer-based embeddings to find conceptually related content, even when the exact words differ. Deployed as a self-hosted service with a clean API.
Press
- Startup Uses AI to Fix Enterprise Search TechCrunch