AI Chatbot for Customer Support
A RAG knowledge assistant grounded in the company's help center and policies, deflecting repetitive tickets and giving agents instant, cited answers.
The challenge
A growing B2B SaaS support team was answering the same product questions over and over. Knowledge was spread across a help center, internal policy docs, and the heads of a few senior agents. New hires took weeks to ramp, and response times climbed during busy periods.
The numbers below are representative of this type of engagement. Real figures are shared with prospective clients under NDA.
What we built
We built a retrieval-augmented knowledge assistant that:
- Ingested the public help center, internal SOPs, and past resolved tickets
- Answered questions with citations back to the source document
- Enforced which content was customer-facing vs. internal-only
- Surfaced "answer gaps" — questions the knowledge base couldn't answer well
The assistant was embedded both in the customer help widget and in the agents' internal console.
The approach
- Content audit to find authoritative, up-to-date sources
- Ingestion pipeline with scheduled re-syncing
- Retrieval + re-ranking tuned against a labeled evaluation set
- Guardrails so the assistant defers instead of guessing
- Analytics on deflection, satisfaction, and content gaps
Results
By grounding answers in real content and measuring quality before launch, the assistant deflected a meaningful share of repetitive tickets and cut first response times — while giving agents faster, cited answers.
Stack
Technology used
RAG Chatbots
Knowledge assistants that answer from your documents — accurately, with sources.