Measure what ships and sticks
Flow doesn't grade engineers. It measures whether work ships and whether it sticks, regardless of how the work gets done. Six dimensions, multi-signal scoring that resists gaming, and health scores that show whether your changes are working.
6 dimensions · no keystroke tracking · private by default
See whether you're improving
score 0–100 · graded A–FA single score that reflects how your team is operating across velocity, quality, delivery, and collaboration. The feedback loop your retros have been missing.
The score is a trend line, not a leaderboard. It exists to answer one question: did the thing you changed last sprint actually move the needle?
See how your team is performing right now, broken down by what matters most, and whether the direction is up, flat, or sliding.
+16 points over 6 sprints
The six dimensions
multi-signal · resists gamingEach dimension reveals a different aspect of how your team works. Together, they show where you're thriving and where there's friction.
Delivery
4 signalsWork ships and sticks
Completion rate · Predictability · Low rework · Deploy frequency
Flow
5 signalsSustainable efficiency
Cycle time · WIP control · Batch size · Focus discipline · Lead time
Quality
5 signalsProductivity creates durable value
Defect density · Stability · Bug fix ratio · Change failure rate · Recovery time
Collaboration
3 signalsAmplifies team output
Review contribution · Responsiveness · Unblocking
Ownership
3 signalsResponsibility over areas
Code depth · Maintenance · Impact scope
Adaptability
3 signalsResponsiveness to change
Response to change · Recovery speed · Resilience
Beyond DORA
deploys · lead time · CFR · MTTRDORA metrics are the industry standard for deployment performance, but they're lagging indicators: they tell you what happened, not what to change. Flow connects DORA signals to the behavioral patterns that drive them.
Deployment frequency dropped
CollaborationFlow shows a review bottleneck: average PR wait time jumped from 4h to 18h this sprint.Change failure rate spiked
Quality + FlowFlow shows batch size creep: average PR size doubled and QA coverage dropped.Lead time is increasing
FlowFlow shows WIP overload: 3 devs carrying 4+ concurrent items, cycle time ballooning.
Diagnoses shown are examples. DORA metrics feed directly into the Delivery, Flow, and Quality dimensions.
Powered by your existing tools
16 integrationsEffectiveness scores are derived from real signals across your PM tools, code repositories, and CI/CD pipelines. No manual input, no surveys — just outcomes.
PM tools
feeds Delivery · Ownership · AdaptabilityIssue completion, estimation accuracy, sprint predictability, and rework rates from Jira, Linear, ClickUp, and more.Code repositories
feeds Flow · Quality · CollaborationCommit frequency, PR review time, code churn, and collaboration patterns from GitHub, GitLab, and Bitbucket.CI/CD pipelines
feeds Delivery · Flow · QualityDORA metrics from your existing pipeline runs: deployment frequency, lead time, change failure rate, and MTTR.
Coaching, not leaderboards
private by defaultTeam retrospectives become individual growth opportunities. AI generates private coaching observations visible only to the developer and, optionally, their manager.
Strength
Sarah's estimation accuracy this sprint was 91%, one of the strongest signals on the team. Worth exploring in a 1-on-1.
Growth area
PR sizes trending larger (avg 450 lines). Discuss smaller incremental changes in the next 1-on-1.
Recognition
Led the migration project with zero production incidents. Strong documentation habits.
Private by default
Coaching notes never appear on the public board.Three visibility levels
Self, manager, admin. Nothing broader.Builds context
Notes from each retro accumulate, sprint by sprint.AI-assisted
Strengths, growth areas, and recognition, drafted for review.
See how your team clicks
one report per sprintYour team dashboard shows collective patterns: where you're strong, where you're struggling, and what to discuss in your next retro.
Team effectiveness
Sprint 24 · Dec 9–20, 2025 · exampleTeam completing 85% of committed work
PRs merging faster since pairing increased
Low bug rate this sprint, a strong stability signal
Balanced performance across key areas
Review turnaround improved to under 4 hours
Good balance of new work and maintenance
Suggested retro topic
Ownership score is lower than other dimensions. Consider discussing how to balance new feature work with tech debt.
From data to action
3 steps · every sprintEffectiveness metrics power better retro conversations. Health scores show whether those conversations led to change.
- 01
See patterns
Your sprint data surfaces what's really happening: review bottlenecks, scope creep, quality dips. - 02
Discuss together
Use concrete data as a starting point. No more “I feel” — now it's “the data shows.” - 03
Track progress
Next sprint, see if your changes worked. Build on what helps, drop what doesn't.
Questions you can finally answer
When teams understand how they work, they can decide how to improve.
- Why do we always miss the last day of the sprint?
- Who's getting blocked waiting on reviews?
- Are we taking on too much unplanned work?
- Is our quality improving or sliding?
- Are we getting better at estimating, or still guessing?
Team data, not surveillance
no keystroke trackingEffectiveness metrics are about how the team works, not ranking individuals. No leaderboards, no top-performer lists. Trust enables honest retros; surveillance kills them.
- Team-level insights for retro discussions
- Individual profiles private by default
- Focus on process improvement, not blame
- Coaching notes visible only to you
Signals, not verdicts
confidence-gated scoringEffectiveness scores are risk indicators, not performance reviews. The model surfaces patterns; it doesn't rank people.
Multi-dimensional scoring
Six dimensions resist gaming: optimizing one at the expense of the others surfaces immediately.Confidence gating
Scores are suppressed when signal quality is low. No false precision from sparse data.Weighted and adaptive
Dimensions weight dynamically based on available signals. Not all teams have all data.Anti-surveillance by design
No keystroke tracking, no activity monitoring. Outcomes and patterns only.
Two audiences, one model
team view · org viewThe same signal model that helps your team improve gives leadership the pattern visibility they need, without micromanagement.
For teams
See whether your retro actions are moving the needle. Health scores across six dimensions give your team a shared language for improvement.
- Sprint-by-sprint dimension breakdown
- Private coaching notes for individuals
- Anomaly detection when patterns shift
For leadership
Know whether your engineering teams are stable, volatile, or trending. Cross-team comparison and risk surfacing, no Jira login required.
- Cross-team health grid at a glance
- Org-level velocity and quality overview
- Executive summaries for stakeholders
Your AI can query these metrics
17 tools · 8 domainsHealth scores, velocity trends, coaching insights: accessible from any MCP-compatible AI assistant. The tools you're adopting can see whether they're helping.
Stop guessing. Start measuring.
Give your team the feedback loop to know whether changes are shipping and sticking — and give leadership the visibility to know whether engineering is stable, volatile, or trending.