RAG AI Knowledge Chatbot
A chatbot that retrieves from your own documents and answers with citations, not guesses.
Based on typical outcomes for comparable systems, not a guarantee.
The same questions keep surfacing across Slack and email, and the real answers are scattered across PDFs, docs, and old tickets. Generic AI chatbots hallucinate confidently when they have no access to the actual source material.
A retrieval system that ingests your documents on a schedule, embeds and indexes them, retrieves the most relevant chunks for each question, reranks them for precision, and answers with inline citations back to source.
Real improvements, not just automation
Here's exactly what changes for your business when this system is running.
Stop answering the same questions over and over. Point people at a chatbot that actually knows your material.
Every answer comes with a citation back to the source document, so your team can verify instead of just trusting.
Cuts down on hallucinated answers by refusing to answer outside what it can actually retrieve.
Feedback (thumbs up/down) feeds back into evaluation, so accuracy improves over time instead of drifting.
Scales to any volume of questions without adding support headcount.
Teams with a large, scattered knowledge base of SOPs, product docs, and past tickets who want accurate answers people can find themselves instead of a generic chatbot that guesses.
How the system works
A full walkthrough of every automated step, from the trigger through to the outcome.
- Step 1Documents ingested on a scheduled job
- Step 2Content is chunked (~500 tokens, with 50 tokens of overlap) and embedded
- Step 3Embeddings indexed in a vector database
- Step 4Incoming question is embedded and matched against the closest scoring chunks
- Step 5Results are reranked for precision
- Step 6Answer generated with inline citations back to source
- Step 7Query, response, and sources logged for evaluation
What makes this premium
This isn't a basic template. Here's what sets it apart.
Answers are restricted to retrieved context only. "I don't know" is an accepted answer, and every factual claim requires a citation.
Reranking trades a little latency for real precision, because accuracy comes first.
Let's build this for your business.
Book a strategy call. We scope the workflow, define outcomes, then build with clear delivery milestones.