10k SLOC/week with Claude.Engineered? Or, slop?
Xpoze measures the engineering quality of your code, so you know whether AI-written code is holding up: measured against published research, not guessed.
Is quality being traded for speed? Nobody can settle it today.
Coding agents raised the volume of change faster than senior engineers can review its design. Leadership has volume numbers. Engineers have a suspicion.
"Pull requests are up. Lines changed per week are up. We're shipping faster than ever."
But volume says nothing about quality, and without a measure of it, volume is all a leader can report.
"Corners are being cut. The design is eroding, and nobody upstairs can see it."
But a suspicion is easy to dismiss, and a pull request reviewer only ever sees one change at a time.
Xpoze settles it with evidence, not opinion.
Leaders keep the productivity gains knowingly. Engineers' concerns rest on evidence. And no rating ever points at a person.
of engineering leaders name impact on code maintainability as their top AI concern.
LeadDev Engineering Leadership Report 2026use change-failure or revert rates to measure AI's impact. Most rely on employee feedback.
LeadDev Engineering Leadership Report 2026is the effective false-positive rate above which developers start ignoring an analyzer.
Sadowski et al., Lessons from building static analysis tools at Google, CACM 2018An answer you can defend, and evidence engineers trust.
Quality, and which way it's moving
Across your codebase and down to each pull request, so leaders see the direction and engineers see the effect of their change.
Specific findings, with evidence
Every finding points at the code and shows the evidence behind it. Few and precise: Xpoze stays silent unless it's sure.
One picture for everyone
Leaders, managers and engineers read the same evidence at their own level. Never a leaderboard, because Xpoze never measures people.
Every rating is grounded in published research, not in an LLM's opinion.
See it on your codeSafe to run, and safe to show.
Every one of these is a design rule, not a setting.
Your code stays in your network
Nothing reaches xpoze.ai: no code, no findings, no telemetry, no license call-home.
Your own LLM
An account with a provider you already approved, or a model you host. It sees no more than your coding agents already send.
Light to run
One container and no database, on your Kubernetes, including managed services such as EKS, AKS and GKE, or as a VM image.
Never measures people
No per-engineer ratings, no productivity figures, no blame. Xpoze measures code, whoever wrote it.
Never blocks a merge
Results are advisory. One link on each pull request, updated in place, never a stream of comments.
Never changes your code
Xpoze writes nothing into your repositories. It reports; engineers and agents act.
A free beta, a few teams at a time.
Request beta access.
The beta is open to a small number of teams at a time. Email us and we'll walk you through it on a call.
- Your team ships code written with AI coding agents
- You want to know whether quality is holding up
One-time setup.
A step added to your CI, and one container you host. No work per repository, and nothing to install on developers' machines.
Questions first? Read the FAQQuestions engineering leaders ask.
Does any of our code leave our network?
No. Xpoze runs entirely in your environment. Neither code nor findings reach xpoze.ai, and it sends no telemetry.
Which LLM does it use?
Yours: an account with a provider you have already approved, or a model you host. What reaches the model is no more than your coding agents already send, with values that look like credentials removed.
Can it be used to rank engineers?
No. Xpoze keeps no per-person ratings or productivity figures. It measures code, whoever or whatever wrote it.
What does it take to run?
A step added to your CI and one container you host, with no database. Run it on your Kubernetes, including managed services such as EKS, AKS and GKE, or as a VM image. Setup is one-time work, with nothing per repository.
Won't it flood our pull requests with comments?
No. It posts one link per pull request and updates it on every push. It never blocks a merge.
How is it different from code-quality platforms or AI code reviewers?
Code-quality platforms count rule breaches, and AI reviewers comment on one change at a time. Xpoze measures the engineering quality of your whole codebase and which way it is moving, and judges each change in that context. It complements both.
Find out whether it's engineered, or slop.
Measured against published research. In your environment, with your LLM.