Now in early access

Your code ships faster.
Your pipeline doesn't.

TimeLeak shows engineering leads exactly where delivery slows down — PR review lag, ticket handoffs, and cycle time by team — pulled directly from Jira and GitHub with no manual setup.

No credit card. No process changes.
Connects via OAuth — your data stays in your stack.

Sprint 47 — Engineering Core Live
Cycle time
3.4d
↓ 18% vs last sprint
Avg review time
6.2h
P90: 22h — 1 team
Change fail rate
4.1%
DORA Elite
INFRA-88 Migrate auth tokens to new provider Stalled 22h
DB-57 Optimise query planner for reporting Blocked 17h
API-122 Add rate limiting to webhook endpoints On track 3.1h

INFRA-88 flagged after 8h with no review activity. The assigned reviewer currently has 6 open PRs.


AI is writing code faster than
your pipeline can ship it.

The constraint in most engineering orgs has shifted. The bottleneck isn't the code anymore — it's everything around it. Reviews that pile up. Tickets that stall between stages. Work that moves backwards late in the cycle.

01

Review queues that silently block delivery

Two or three overloaded reviewers can slow down an entire team without it ever showing up in a retro. You see the symptom — missed velocity — but not the cause.

02

Tickets that disappear between stages

Cycle time from dev to release often contains hours of invisible waiting. Work sits in handoffs that don't appear on any board, in any report, or in any standup.

03

Delivery data that's always a sprint behind

Retros happen after the damage is done. By the time you identify a bottleneck from sprint data, the same issue has already slowed the current one.


Up and running in under five minutes.

1

Connect your tools via OAuth

Link Jira, GitHub, or Bitbucket with a single OAuth handshake. No tokens to manage, no data to export, no infrastructure to set up.

2

Select your projects and repositories

Choose which Jira projects and Git repos to track. TimeLeak builds your baseline from existing workflow data immediately.

3

See live metrics within minutes

Cycle time, PR throughput, review lag, and bottleneck detection are live as soon as your data syncs. No tagging. No process changes.

4

Get alerted before bottlenecks compound

TimeLeak flags stalled PRs and blocked tickets while there's still time to act — not after the sprint post-mortem.

timeleak — sprint analysis
$ timeleak analyze --team engineering-core
// Fetching sprint 47 data...
cycle_time_avg 3.4d // ↓ 18% vs sprint 46
pr_throughput 24 // merged this sprint
review_wait_p90 14.2h // ↑ needs attention
velocity 82pts // ↓ 4 from forecast
// Bottlenecks detected
bottleneck "INFRA-88" // 22h in review
bottleneck "DB-57" // blocked — auth team
$ _
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Every metric that matters
to engineering leadership.

Built from real Jira and Git signals — not estimates, not manual input. All 14+ metrics update automatically from your existing workflow.

Cycle time
3.4d
End-to-end from dev start to release, broken down by stage: dev, test, release.
Review lag
6.2h
Average, median, and P90 PR review times. Spot overloaded reviewers before they block delivery.
DORA metrics
Elite
Lead time, deployment frequency, change failure rate, and MTTR — auto-classified by DORA tier.
PR throughput
24
PRs merged per sprint by team. Compare teams side-by-side to find high-performing patterns.
DORA tiers
Elite Deploy on demand, <1h lead time
High Weekly deploys, <1 week lead time
Medium Monthly, 1–6 months lead time
End-to-end cycle time (dev → release)
Lead time for changes (ticket → production)
Review time — avg, median, and P90
PR throughput and merge rates
Ticket lifecycle breakdown by stage
Change failure rate (tickets moving backwards)
Sprint velocity by team
Avg PR size — flagged when oversized

Stop guessing where
the time goes.

Join the waitlist and get first access when TimeLeak opens to early teams. We'll reach out personally before onboarding.

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