Enterprise Knowledge Engines Over Proprietary Datasets

Internal company data is fragmented.

Your team loses hundreds of billable hours searching across scattered PDF contracts, old support tickets, Google Drive folders, and internal databases using basic keyword search tools that fail to understand conceptual meaning. We unlock company knowledge.

We build custom Retrieval-Augmented Generation (RAG) pipelines that enable natural language question-answering over your company data. By combining dense semantic embeddings with BM25 keyword matching and cross-encoder rerankers, we deliver sub-second answer retrieval with exact source citations.

RAG Pipeline Specifications

• Hybrid Retrieval Engines: Combining PostgreSQL pgvector dense search with BM25 lexical search to catch exact serial numbers and conceptual matches.
• Cross-Encoder Reranking: Passing retrieved candidate chunks through dedicated rerankers to ensure only the highest-relevance context reaches the LLM.
• Hallucination Evaluation: Continuous benchmarking using the Ragas framework to guarantee context recall and factual precision.

Turn raw documents into actionable intelligence with TechnologyBae on our Contact Us page.