Cutting Support Drafting Time with a RAG Support Copilot (Bengaluru SaaS)
How a Bengaluru B2B SaaS cut support drafting time by 50-70% with grounded AI.
The Problem
A Bengaluru B2B SaaS company had support reps searching through Slack, Notion, old tickets, and runbooks for every customer question.
Generic chatbot tests hallucinated policies. Manual responses were slow and inconsistent.
- ×Support hopping between 4-5 tools to answer each question
- ×Long response times and inconsistent answers
- ×Generic chatbots that hallucinated or broke policy
- ×New hires took months to learn the product
Our Approach
We built a RAG Support Copilot that generates grounded answer drafts from internal docs, with human-in-the-loop approval.
1Index All Knowledge Sources
Built a RAG index over docs, FAQs, runbooks, past tickets, and golden replies—everything support needed but couldn't easily search.
2Create Copilot in Helpdesk
Integrated copilot into their helpdesk—reads ticket, generates draft answer from RAG, suggests next steps. Human approves before sending.
3Implement Feedback Loop
Approved answers get fed back into the RAG corpus. System learns from what support actually sends, not just static docs.
4Add Guardrails
Copilot only answers from indexed docs. If answer isn't grounded, it escalates to senior support. No hallucinations.
The Results
"It's the first AI tool we've used that actually respects our docs instead of making stuff up. Support reps love it because it makes them faster, not replaceable."
— Head of Support, Bengaluru B2B SaaS
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