AI Chatbots That Know Your Business
Retrieval-Augmented Generation (RAG) chatbots trained on your proprietary data to provide accurate, hallucination-free answers with citations.
What It Is
We design robust enterprise RAG architecture to power intelligent, secure RAG chatbots on premise and in the cloud. By building a custom AI chatbot with citations, we ensure it answers questions specifically from your own data corpus—be it PDFs, internal wikis, or technical documentation. If you need a reliable AI chatbot for internal documents, we implement state-of-the-art chunking strategies and robust vector databases to guarantee precise answers and eliminate hallucinations.
What's Included
Comprehensive solutions tailored to your needs
Data Processing Pipeline
Extract, clean, and chunk text from PDFs, Notion, Confluence, and websites.
Vector Database Setup
Implement scalable semantic search using Pinecone, Qdrant, or pgvector.
Citation & Source Tracking
Every answer includes links to the exact source document and page number.
Hybrid Search
Combine keyword (BM25) and semantic search for unparalleled retrieval accuracy.
Real World Impact
Legal Tech Firm
The Problem
Lawyers spent hours manually searching through thousands of pages of case law and internal memos to find relevant precedents.
The Solution
Built a secure RAG chatbot application. Ingested 50,000+ legal documents using semantic chunking and deployed a hybrid search vector store. The chatbot provides answers strictly grounded in the uploaded documents.
The Result
Reduced document discovery time from hours to minutes, increasing lawyer billable efficiency by 20%.