Problem
Support drowned in repeat questions already answered in the docs, while genuinely hard tickets waited behind them. Canned macros did not help because customers asked in their own words.
Case studies / SaaS / Software
An AI agent that answers from the docs, and escalates when it should not guess
SaaS / Software · Head of Support
DwgWhat we built
SheetSaaS / Software
Steps04
What we built
Build
- A retrieval agent grounded in the product docs, changelog, and past resolved tickets.
- It answers in the help widget with citations, and hands off to a human the moment confidence drops or the question touches billing or account access.
- Every answer is logged with the sources it used.
Stack
- RAG pipeline
- Frontier LLMs
- Vector search
- Helpdesk API
Result
Documented questions get answered by the agent whenever they arrive, so the team spends its day on tickets that need a person. Escalations arrive with the conversation history already attached.
Before and after
Outcome
Documented questions
Answered by agent
Answers
Cited to source
Uncertain answers
Escalated, not guessed
Track record
6+
Years building automation
500+
Client reviews (4.9 avg)
650+
Projects delivered
A pattern we build often. Outcomes describe the system and how it changes the work, de-identified for privacy. Named references for your industry are available on request under a mutual NDA.
More case studies
All case studies →Continues · Book a consultation
Have a similar problem to solve?
Book a paid consultation. We'll diagnose your situation against patterns we've seen and hand you a concrete plan.
Book a consultation
We typically respond within 24 hours