Key Benefits

Natural language search

Across all your internal documents — policies, contracts, manuals, case files — without manual keyword matching

Accurate, sourced answers

With citations back to the original document — not hallucinated responses

Qdrant vector database

Stores and retrieves semantically relevant content, not just keyword matches

Incremental ingestion

new documents added to the knowledge base automatically without rebuilding the entire index

Role-based access control

Ensures staff only retrieve content appropriate to their permission level

Full JavaScript/Node.js stack

Integrates cleanly with your existing backend without a Python dependency

Stack

Technologies Used

LangChain.js
Qdrant Vector Database
Azure OpenAI Service
LangChain.js
Qdrant Vector Database
Azure OpenAI Service
Node.js / TypeScript
Azure Blob Storage
Node.js / TypeScript
Azure Blob Storage

Have a large document library that your team struggles to search effectively? Our 2-week AI Discovery Workshop assesses your content, defines the retrieval architecture, and produces a fixed-fee build plan before any development begins.

Faqs

Frequently Asked Questions