For product companies
Dozens of developers across departments — and AI coding agents — commit to one product every day. Pickvy gives you a single, current, business-readable verdict on all of it, so quality stops drifting and every release stops being a leap of faith.
The reality
Backend, frontend, mobile, data — plus AI coding agents — all push into the same codebase. Velocity is up; shared visibility is down. No single person can say, on any given day, how healthy the product actually is.
58% of developers now use AI regularly and 78% worry the output is wrong — that risk is already inside your product.
The core problem
As code scales across departments, quality drifts, tech debt hides, and each release becomes guesswork. The moments that should be checkpoints turn into blind spots.
PROBLEM 01
Each squad has its own conventions and its own idea of “good enough.” Standards drift between departments, and no one owns quality across the whole product — so the weakest module quietly sets your real risk.
One objective Health Score on the same rubric for every team and module — healthy / stabilize / dangerous, per-team and whole-product. See exactly where the product is strong and where it's fragile, and hold every department to the same line.
PROBLEM 02
Developers across teams lean on AI coding agents. It ships fast and looks fine, but it carries a new, opaque category of risk that normal review skims past — and nobody can tell you how much AI-origin code is in the product or where it's dangerous.
Pickvy specializes in auditing AI-generated code. It surfaces the risky, AI-shaped patterns reviewers miss, and lets you set rules for AI agents on every PR — so speed doesn't quietly turn into liability.
PROBLEM 03
Go/no-go is a gut call. Nobody can prove a release is ready, or show whether health improved or regressed since the previous version — until something breaks in production.
A deterministic Health Score with explainable changes between releases, and launch-blockers ranked first. Turn every release into an objective go/no-go, and prove — in numbers — that the product is getting healthier, not just bigger.
And more
An objective map of where debt is worst, ranked — so engineering time goes to what actually moves risk.
An instant map of a module's riskiest files and structure cuts ramp-up on unfamiliar code.
Dependency, secret, and vulnerability scanning (OSV, Semgrep) across every team's code.
An owner-neutral, objective view ends cross-department finger-pointing over quality.
A business-readable verdict and PDF your PMs, execs, and department heads all understand.
Objective code-health evidence ready the day you fundraise or get audited.
The product
Pickvy audits any codebase — AI-generated or not — and answers the question a PM and an engineer both understand: is it healthy, does it need stabilization, or is it already dangerous? Every finding carries a measurable score, a priority, and a fix plan with a cost.
In your workflow
Plug Pickvy into the pipeline every team already uses — GitHub / GitLab — and make health a continuous signal, not a quarterly scramble.
What you get
| When | What Pickvy gives you |
|---|---|
| Across departments | One Health Score on the same rubric — per-team and whole-product |
| On every PR | Automated checks + rules for AI-generated code |
| Before a release | A go/no-go readiness verdict with blockers ranked |
| Between releases | Explainable score changes, so you catch drift early |
| For execs & PMs | A business-readable report and PDF |
The Enterprise plan adds private / self-hosted deployment, custom rules, SSO, roles & teams, an audit trail, PR-control, and score history across the whole product.
Why Pickvy
One rubric, owner-neutral — no team grading its own homework, no arguments about whose module is worse.
Health becomes a live signal on every PR and release — not a scramble before an audit.
A verdict and a cost your PMs and execs understand — not a raw linter dump.
Your product ships every week, built by more people than any one person can review. Pickvy gives you one honest number for all of it — start with a Diagnostic Report on your main repo.