Turn your data into engineering decisions.
Most teams guess where their engineering time goes. Cocollabs knows. Cycle time, review health, and investment patterns, straight from your code.
| Team | AI Adoption | PRs/Eng | Cycle Time | Δ MoM |
|---|---|---|---|---|
| Platform | 84% | 4.2 | 0.9d | -31% |
| Frontend | 71% | 3.8 | 1.1d | -24% |
| Backend | 58% | 3.1 | 1.4d | -18% |
| Data/ML | 43% | 2.4 | 1.8d | -9% |
| Team | AI Adoption | PRs/Eng | Cycle Time | Δ MoM |
|---|---|---|---|---|
| Platform | 84% | 4.2 | 0.9d | -31% |
| Frontend | 71% | 3.8 | 1.1d | -24% |
| Backend | 58% | 3.1 | 1.4d | -18% |
| Data/ML | 43% | 2.4 | 1.8d | -9% |
Four signals your team needs every week
Each one derived from your actual code changes.
Engineering Investment Breakdown
See exactly where time goes. Every PR classified as Feature, Bug, or KTLO automatically from code diffs, not titles or labels.
PRs classified
128
This week
14
Confidence
96%
Team Output Trends
See what your team actually ships each week — broken down by feature, bug, and maintenance. Spot output dips before they become delivery risks.
PRs shipped
247
+18%Lines merged
32.4K
+12%Contributors
14
+2Review Flow Health
Identify stuck PRs, overloaded reviewers, and the specific bottlenecks slowing your team. Surface what's blocking before it compounds.
Weekly Engineering Digest
AI-generated narrative of everything you shipped, reviewed, and where your time went. Ready for standups, 1:1s, and performance reviews.
Week of Feb 10 - 16
What You Shipped
Payment flow overhaul, auth bug fix, CI config updates
PRs merged
4
Lines shipped
929
Cycle time
14h
The metrics that actually change how you ship
Go beyond vanity dashboards. Cocollabs surfaces the bottlenecks and patterns hiding in your PR data.
Cycle Time Breakdown
Last 30 days
W1
40% wait
W2
48% wait
W3
42% wait
W4
49% wait
Median cycle time
3.7d
PRs this month
142
Longest stage
Review
Cycle Time Insights
Average cycle time is a vanity metric. Cocollabs breaks it down by coding time, review wait, and merge queue — so you see exactly which stage is the bottleneck and how it trends week over week.
- End-to-end PR lifecycle: first commit to merge, broken into stages
- Identify whether slowdowns are in coding, review, or deployment
- Week-over-week trend detection catches regressions before they compound
- Filter by team, repository, or PR size to find root causes
Review Load Distribution
Last 30 days
@james is handling 2.4x the team average. 3 PRs are waiting 4+ days for first review.
Review Exposed Bottlenecks
One reviewer handling 60% of reviews. Three PRs stuck for 4+ days. A repo where nothing gets reviewed on Fridays. Cocollabs maps your review network so you see the human bottlenecks, not just the numbers.
- Review load distribution across team members with imbalance alerts
- Stuck PR detection: PRs waiting beyond your team's normal threshold
- Reviewer response time trends — spot burnout before it hits
- Actionable suggestions: who to redistribute reviews to
Connect once, see everything
Full engineering visibility, all in one place.
Connect your repositories and see your real engineering investment breakdown — features, bugs, and maintenance — in 30 seconds.