B2B SaaS / DevToolsAI Agents & AutomationCustom AI Apps & Chatbots

Auto Issue Resolution: Chatbot + Claude Code

Fixed-fee Sprint + Hourly support

12 min

Average ticket → merged PR time (down from ~6 days)

The challenge

A fast-growing dev-tools SaaS had a brutal support-to-engineering loop. Customer reports a bug → support reproduces → files a Jira ticket → 2-5 days later someone picks it up → fix lands a week+ later. Most tickets were small but they crowded the backlog.

The approach

Stage one: customer-facing chatbot for triage and reproduction
Stage two: Claude Code in a sandboxed environment writes fixes and submits PRs
Tight guardrails — max 50 LOC, no schema migrations, allowlist of touchable directories

The build

Triage chatbot embedded in the in-app help widget, with extended diagnostics SDK
Issue classifier routes tickets into 5 buckets (low-complexity / config / docs gap / feature request / human)
Autonomous fix runner: Claude Code in Docker sandbox with scoped repo access
Guardrails: 50 LOC max, no auth/security files, no major dependency upgrades
Every PR gets human review — measured human approval rate weekly

The results

Average ticket → merged PR: 12 minutes (from ~6 days)
Human approval rate on autonomous PRs: 84%
44% of all incoming tickets resolved end-to-end
Reclaimed ~28 engineering hours/week
Zero security incidents in 120 days
Customer CSAT on bugs up from 3.6 → 4.7

"The first time I saw a Claude-Code-authored PR ship to production with no human edits, I was nervous. 90 days later I think about it the same way I think about any other contributor."

— VP of Engineering