Chatwoot Engineering Benchmarks
Chatwoot delivery benchmarks are based on 82 merged pull requests in the last 30 days (397 all-time), with 22.2 hours median cycle time, 0.3 hours median review time, and 14 active contributors. AI-related signals appear on 1.2% of recent work. PR volume is up 71% compared to the prior period.
Repo vs Chatwoot Average
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Cycle Time by AI-Related Signals
PR Breakdown
Top AI Tools
PR Type Breakdown
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| revert: restore conversation unread count feature flag | sony-mathew | — |
| feat(whatsapp): add support for voice messages | gabrieljablonski | — |
| feat(onboarding): honor return_to hint in Instagram OAuth c… | scmmishra | — |
| feat(conversations): remove unread count feature flag (CW-7… | sony-mathew | — |
| docs: document message attachment uploads | sojan-official | — |
Methodology
Metrics are computed from merged pull request data synced daily from GitHub. AI-related metrics are directional signals inferred from pull request activity patterns and heuristics. Summary metrics use a 30-day rolling window; trends use a 90-day window. Last updated 16 hours, 28 minutes ago.
Updated daily from public GitHub pull requests.
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