Engineering delivery metrics

Trace every change from commit to production.

Throughline reads your Git, CI, and code review data and turns it into the four signals that predict delivery — cycle time, deploy frequency, PR throughput, and lead time. See exactly which stage is slowing you down, and prove it with data.

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throughline — Platform team
Cycle time · last 30 days
4.2h
18%
Deploys
9.3/d
PRs
47/wk
Review
3.1h
The throughline

Measured at every stage, from keyboard to production

Commit312 / wk
PR opened47 / wk
Review3.1h median
Merge94% < 1 day
Deploy9.3 / day

Trusted by platform & delivery teams at

The problem

Velocity charts don't tell you where to look.

Story points measure estimates, not flow. Dashboards bolted onto your issue tracker miss the half of delivery that happens in Git and CI. So when the board says "on track" but releases keep slipping, you're left arguing from anecdotes.

Throughline connects the system of record you already have — commits, pull requests, pipelines, deploys — and shows you the one stage that's actually costing you the week.

How the metrics work
Where the week goes · Platform team
Coding2.1h
Review wait Bottleneck14.2h p95
CI & checks24m
Deploy to prod1.2h

Review wait is 5.8× your median coding time. Throughline flags it automatically.

What you get

Four metrics. One source of truth. Zero spreadsheets.

Every signal is computed from the events your tools already emit — no agents to install, no manual logging, no story-point math.

01 / Metrics

The four delivery signals, computed continuously

Cycle time, deployment frequency, PR throughput, and lead time for changes — the metrics research ties to elite delivery. Throughline derives each one from your actual Git and CI history, recomputed on every event.

  • No estimates, no self-reporting — events only
  • Per-team, per-repo, and org-wide rollups
  • Benchmarked against your own 90-day baseline
Cycle time 18%
4.2h
Deploy freq 12%
9.3/d
PR throughput 6%
47/wk
Lead time 9%
1.8d
02 / Bottlenecks

Find the stage that's actually costing you

Throughline breaks every change into stages — coding, review wait, CI, deploy — and surfaces the p50 and p95 for each. The slowest stage gets flagged, so you fix the bottleneck instead of pushing everyone to "go faster."

  • p50 and p95 per stage, not just averages
  • Automatic flagging when a stage dominates
  • Drill into the exact PRs behind the number
Stagep50p95
Coding2.1h6.4h
Review wait Flagged3.1h14.2h
CI & checks11m24m
Deploy to prod18m1.2h
03 / Trends

Trends that survive a board review

Every chart compares the current window to your rolling baseline and to the team average — so a number is never just a number. Export any view to a slide, or pipe it straight into your weekly delivery report.

  • Baseline + team-average comparison on every chart
  • Annotations for incidents, freezes, and releases
  • One-click export to slides and Slack
Cycle time · 12 weeks This teamOrg avg
Inside Throughline

The dashboard your staff engineers keep open

Drawn from real delivery data — no screenshots, no mockups. This is the view your leads see every morning.

app.throughline.dev / overview
Platform team Last 30 days
Cycle time 18%
4.2h
Deploy freq 12%
9.3/d
PR throughput 6%
47/wk
Lead time 9%
1.8d
Cycle time trend
Deploys per day

Mon → Fri, trailing 12 days

Why teams switch
We cut review wait from two days to four hours — because Throughline showed us review was the bottleneck, not coding speed. It paid for itself in a quarter.
Dana Okafor
VP of Engineering, Parabola
Pricing

Start free. Upgrade when it earns its place.

Connect a repo and see your metrics today — no card, no sales call. Move to Team when you want history, comparisons, and unlimited seats.

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1 team, 14-day history
$0
Team
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$49/mo
Enterprise
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Custom
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Stop guessing how your team ships.

Book a 30-minute demo. We'll connect a repo live and show you your real cycle time before the call ends.