Teams that ship better with Throughline.
Engineering leads use Throughline to find the stage that's actually slowing them down — and then prove the improvement. These are three teams that did exactly that.
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What teams see after connecting Throughline
Medians across teams active for 90 days or more. Numbers are from real delivery data — not surveys, not estimates.
Median drop over 90 days from baseline
More frequent production deploys
At the 95th percentile, across all PR sizes
Faster lead time from first commit to prod
Releases were slipping. The board said they were on track.
The challenge
Loamworks ships routing and dispatch software to regional freight carriers. Their 38-engineer team was running two-week sprints that routinely took three. Story-point burndown charts showed 90% completion going into release week — but features kept landing late, and the ops team was fielding customer escalations about delayed fixes. The VP of Engineering suspected review wait but had no data to back it up in planning.
What they did
Within a week of connecting Throughline, the bottleneck surfaced: review wait sat at 18.4h at the p95, nearly triple the time spent coding. The team introduced a review-pairing rotation and capped PR size at 400 lines. Throughline's stage breakdown made the change visible immediately — and gave the eng lead a number to bring to the next planning meeting instead of a feeling.
"I'd been telling the team to write smaller PRs for two years. Throughline showed everyone the actual data — 18 hours waiting for review on a change that took 2 hours to write. That number did more than any process doc ever did."
| Stage | Before | After |
|---|---|---|
| Coding | 3.4h | 3.1h |
| Review wait Was bottleneck | 18.4h | 4.8h |
| CI & checks | 18m | 22m |
| Deploy to prod | 1.4h | 1.1h |
Lead time was 10 days. Compliance said it had to be 3.
The challenge
Tidewell builds payment orchestration APIs for mid-market lenders. A PCI audit flagged their change lead time — at the time averaging 10.4 days — as a material risk indicator: slow, infrequent deploys meant fixes sat in branches longer and audit trails were harder to close. Their new CISO gave the engineering org six months to bring lead time under four days. No one knew where to start.
What they did
Throughline's stage breakdown showed that most of the 10.4-day lead time wasn't in review or CI — it was in branch age. Changes were sitting in long-lived feature branches for an average of 6.8 days before a PR was opened at all. The team moved to trunk-based development with feature flags over eight weeks. Throughline's trend view let the CISO track progress week-over-week without a manual report. Lead time dropped to 3.2 days — below the four-day target — within 16 weeks.
"We needed a number, a trend, and a clear owner. Throughline gave us all three in the first week. Our CISO closed the audit finding two months ahead of schedule."
Board said on track. Customers felt every slip.
The challenge
Parabola builds a visual data pipeline tool used by operations teams at growth-stage companies. Their 24-engineer org was shipping features on a monthly cadence — but hotfixes were taking two to three days to reach production, which meant customers were hitting bugs over multiple work days. The engineering team suspected their CI configuration had gotten unwieldy, but had no data to support rearchitecting it to leadership.
What they did
Throughline's stage breakdown showed CI and checks were not the problem — they ran in under 14 minutes at the median. The actual bottleneck was review wait: the p95 sat at 14.2 hours, and it was highest on the team most responsible for hotfixes. Dana Okafor, VP of Engineering, restructured the on-call rotation to include a dedicated reviewer for high-priority PRs. Review wait dropped to under four hours within six weeks — and cycle time fell from two days to under six hours.
"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."
Review wait is 5.9× coding time. Throughline flagged it on day one.
The bottleneck is almost never what you think.
Across every team that's connected Throughline, the slowest stage consistently surprised the eng lead. Not because their intuition is bad — but because delivery data lives in four different systems and nobody was adding it up. Throughline adds it up.
Connects in minutes
Read-only OAuth to GitHub, GitLab, or Bitbucket. Add your CI provider and you have live metrics on the same day.
Baseline comparison built in
Every metric is compared to your own 90-day rolling baseline. You see the change, not just the number.
Board-ready exports
One-click export to slides or Slack. Bring your delivery trend to the next planning meeting instead of a spreadsheet.
Find your team's bottleneck in a single session.
Book a 30-minute demo. We'll connect a repo live and show you your real cycle time — including which stage is costing you the most — before the call ends.
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