Code got fast.
The process did not.
Ship faster and the bottleneck moves: review queues, a stale roadmap, teams on different priorities. Process checks built by top engineering consultants read your tickets, commits and AI spend every night, so you know where to improve.
Trusted by engineering teams
1 passing · 5 need attention
- 421
Rubber-stamp review on a high-risk change
navigaracom/vision · PR #2004
- 6612
Work shipped under an epic the roadmap never tracked
ENG-2884 · AI Analytics Integrations
- 94
Team sprint spent on a deprioritized initiative
Platform team · sprint 41
- 143
Commit unrelated to the ticket it references
navigaracom/vision · PR #2118
- 3138
Pull request open too long
navigaracom/vision · PR #1908
The constraint moved into the three places nobody instruments.
Output per engineer went up. Review capacity, roadmap upkeep and the work of keeping teams pointed at the same priority did not. Each one gets harder with every team you add.
More pull requests per engineer, the same number of reviewers. Approvals get faster and thinner until the review stops being a control at all.
Delivery moves faster than the board is updated. The roadmap ends up describing a plan the codebase left behind weeks ago.
Every team is busy. Whether they are all busy on the same priority is the question nobody can answer once you pass a handful of teams.
None of this shows up in a velocity chart. It shows up months later, as work nobody asked for and priorities nobody agreed on.
The evidence lives in three systems. All three are ungoverned.
Break one link and the whole chain stops being provable. Process checks read all three every night, on read-only access, and report what slipped.
Read-only · nightly
Intent
Jira
Intent
Linear
Execution
GitHub
Execution
GitLab
Cost
Anthropic
Cost
OpenAI
Checks
Runs nightly
High
Epic with no expected return
Warning
Rubber-stamp review
Info
Spend with no delivery
Why this exists. Who asked. What it is worth.
What actually shipped, and whether it matches the ticket.
What delivery cost in tokens, and what it returned.
What a broken chain looks like.
Every finding carries a severity, a location and an owner. These four are the ones that cost the most.
- High
Epic with no stated customer and no expected return
Intent with no purpose. Nobody can say later whether it was worth building.
- Warning
Ticket attached to no epic
Execution with no intent. Work happened and the roadmap never heard about it.
- Warning
Commit that has nothing to do with the ticket it references
The link is there. The audit trail behind it is fiction.
- Info
Token spend with no delivery behind it
Cost with no return. This is the line item finance asks about.
We did not automate the rules. We automated the reviewer.
No linter can decide that a review was rubber-stamped, or that a commit has nothing to do with the ticket it claims. That takes reading both sides and forming a judgment.
Agents do that nightly, across every repository and every board. Each finding has a severity, a location, an owner and a state.
The same discipline you already apply to bugs, applied to how the work gets done.
The checks were written by the people companies hire to fix this.
Top engineering consultants, fractional CTOs and the leaders who run these turnarounds for a living codified what they look for into checks that keep a process healthy. You start on their judgment, running against your data, not on a blank rule editor.
Day one
Our defaults run against your Jira, your repositories and your spend. Nothing to configure.
Week two
Your rules, your severities, your thresholds. Anything you disagree with, you change.
From then on
Your standards stop being a document nobody opens and start being something with a state.
Every rule, severity and threshold is yours to overwrite. If your team holds a standard we never thought of, it becomes a check.
Left open, every finding turns into a question you cannot answer later.
A thin review, an untracked epic and a team on the wrong priority all leave the same residue: work whose purpose, cost and outcome can no longer be linked back together. Months later that arrives as a question from finance about what the AI spend bought. The data exists. The links between it do not.
Roadmap delivery is the join. Trace a commit to a ticket, a ticket to a priority, and the dollar follows. Checks is what keeps that chain intact.
Every finding you close shows up in your ETV.
This is not a hygiene dashboard. A clean process is the thing that makes performance measurable in the first place. As findings close, the link from a commit to a ticket to a priority holds, and ETV becomes a number you can put in front of a board.
Illustrative
That is the loop. Read the process, rank what slipped, fix the top of the list, and watch the metric move.
See the checks
on your data.
Read-only access. We run the checks against your Jira, your repositories and your AI spend, and walk you through what came back, ranked by severity.
Read-only
No write access to any system.
On your infrastructure
Code never leaves your servers.
Findings, not a report
Ranked, located, assignable.