Enterprise
Document intelligence over one million files
A retrieval augmented generation platform that lets teams search, summarize, and ask questions across more than a million complex documents.
- 1M+ documents processed
- Hybrid semantic and keyword retrieval
- Designed for scale and reliability
The challenge
Critical knowledge was spread across more than a million long and inconsistent documents. Keyword search returned noise, and analysts spent hours locating the right passage before they could even start their work.
Our solution
We built a RAG platform that combines semantic and keyword retrieval with a generative layer that produces context aware answers and summaries. The ingestion pipeline processes documents at scale, and the architecture was designed for high speed operation on very large datasets.
The outcome
Teams now query the full corpus in natural language and receive accurate, context aware answers and summaries, turning a slow manual search into an everyday tool.
