AI / KnowledgeConsulting
RAG Pipeline & Knowledge Assistant
Retrieval-augmented generation (RAG) pipelines that let teams ask questions of their own documents and get accurate, cited answers.
The challenge
Company knowledge is scattered across PDFs, wikis, tickets and drives — so people ask colleagues or search for ages, and generic AI chatbots guess answers.
Our solution
Retrieval-augmented generation (RAG) pipelines that connect LLMs to your company knowledge — PDFs, wikis, tickets and databases. Documents are chunked, embedded and indexed in a vector database, so answers are grounded in your data with source citations.
Key features
- Ingests PDFs, Office files, wikis, help-desk tickets and databases
- Chunks, embeds and indexes content in a vector database
- Answers questions with citations to the source documents
- Respects user permissions and departments
- Evaluation suite to measure answer quality over time
Results
Outcome — Answers grounded in company documents with source citations, so teams find information in seconds instead of searching manually.
