Know what your engineering org actually ships.
Weave looks at every PR and answers one question: how long would this take an expert engineer to complete?
Output trend across the last 13 weeks, benchmarked against peer engineering teams.
Consistent and comparable across individuals, teams, languages, and organizations.
Unlike lines of code or PR count, Weave analyzes the impact of every change, not just how much was written.
The same model runs across every engineer, every repo, every language. No exceptions.
Visualize output across squads. Identify high-performing teams and surface where technical debt or process friction is slowing delivery.
Output per engineer · 30 days
Platform
128
Payments
94
Growth
71
Mobile
52
View output per engineer within a team context. Spot coaching opportunities and recognize your most impactful contributors.
Platform · by engineer
Engineer
Output
Quality
Reverts
M. Chen
142
94
1
R. Mehta
131
92
0
J. Park
118
89
2
S. Tombs
96
91
1
Every incident links back to the commits that shipped before it. Stop reconstructing the timeline by hand.
Incident → cause
Incident
sev-2 · 482
Deploy
2.14.0
Pull request
#1204
See which engineers and repos have the highest revert rates. Catch quality issues before they compound.
Revert rate by repo · 90 days
api-gateway
8.2%
checkout
5.1%
web
3.4%
mobile
2.0%
Spot areas of your codebase with high churn and rising bug rates before they become costly to maintain.
Churn by week · payments
12 weeks ago
Now
Impact Analysis
Score code review quality on depth, thoroughness, and practicality. Keep your review bar high over time instead of letting it silently degrade.
Average review cycles before merge
Track how many rounds of review each PR goes through. Identify bottlenecks and reduce the cycles that slow delivery.
Review volume by team
Break down review volume by team member and week. Balance workload and keep reviews from piling up on your most senior engineers.
Rounds to merge · all repos
1 round
48%
2 rounds
31%
3 rounds
14%
4+ rounds
7%
Reviews per reviewer · weekly
31
22
14
8
Platform
Payments
Growth
Mobile
Deploy MTTR · benchmark tiers
Elite
High
Medium
Low
CI/CD metrics
Mean time to recovery from a failed production deployment. Benchmarked from elite (under 1 hour) to low (over 1 week).
How often your team deploys to production.
Percentage of production deployments that succeed.
Time from code merge to production deployment.
Industry benchmarks
Compare normalized output against real data from thousands of engineering orgs.
Fair comparisons regardless of your team’s scale.
Industry-standard review depth and cycle time benchmarks.
How much of your codebase is being rewritten relative to industry peers.
Track AI-generated code as a percentage of total output. Benchmark against industry peers so you know where your organization stands.
Authorship of merged code · 30 days
AI-assisted 44%
Human 56%
Your org
44%
Peer median
30%
Compare AI-assisted code against actual engineering output across bugs, features, and maintenance. Volume alone doesn’t tell the story. Weave connects AI usage to what actually ships.
AI-assisted share by work type
Features
52%
Maintenance
38%
Bugs
21%
Weave syncs usage metadata from connected IDEs and CLI tools. It attributes code output to either AI or human authorship using advanced heuristics, then correlates AI usage with engineering productivity and cost data to surface the full picture.
AI Efficiency
87
Categorize your tools into foreground AI (interactive tools like Cursor and Claude Code) and background AI (automated agents). See how each category impacts your codebase differently.
Visualize how specific tools influence delivery speed. Correlate adoption of Cursor, Windsurf, Claude Code, and others with actual productivity changes across your team.
Monitor subscription spend per user alongside output data. Make sure your investment in AI tooling aligns with the productivity gains you’re actually seeing.
The engineering intelligence platform for the AI era.
Output, quality, review health, and delivery benchmarks in one place — measured consistently across every team you run.
