Build an Agentic SDLC you can trust.

Read-only access to the repositories your agent works in. Stage one runs entirely on history you already have: PRs, commits, reviews, and the fixes that followed. Later stages add access only when they need it, and you see exactly what each one adds.

Stage one doesn’t wait for new incidents; it runs on history that already exists, so evidence starts arriving as soon as access does. Each stage is scoped in the opening workshop.

Any software engineering agent whose work lands in your repositories: in-house harnesses, Claude Code, Codex, or bought tools. If you don’t run an autonomous coding agent yet, we establish the first one with you.

We’re flexible on where the data lives: bring your own LLM endpoint or use ours. Engagements start read-only, under NDA, and we never train on your code. The trust page covers the rest of what your security team will ask.

A fixed fee for each engagement stage, plus a subscription for the platform. For a longer-term contract, one annual fee covers both. Every price is scoped and set up front in the CTO-led scoping workshop.

Yes. Every prompt tweak, agent change, or model update is measured against the same history, before and after, and the measurement is refreshed as your code evolves. A model update that shifts behavior overnight shows up in the score, not in the bill.

Only where the evidence says it’s safe, the regulatory environment allows it and you want it. Human review load comes down step by step, each step backed by evidence from your own history, and humans keep control throughout.

Measurement only works when it’s independent of the thing measured. We don’t sell you a model, so we have no stake in which one wins: your agents are scored on your outcomes, across whatever models you run, and the numbers stay honest when you switch. Also, the model providers have no incentive to build it: they want to sell you more tokens, not to be independently measured and optimized for fewer tokens or replaced by another model.

You keep everything: the labels, the prompts, the reports. Exportable by design, so leaving is always cheap. We’d rather earn the renewal than lock the door.

Humans decide where agents may merge on their own, and nobody’s personal stats end up on a dashboard.

Evidence from your own SDLC gives teams a reason to adopt instead of a mandate to comply with.

In-house, Claude Code, Codex, or bought: we don’t replace your setup, we measure it and make it better.

Every score traces back to a real PR, fix, or incident in your history. When an agent missed something, reality already wrote it down.

Read-only access to PRs, review comments, code and CI results, on GitHub or GitLab. We never write to your code, and you approve every agent change.

The measurement is built from your own repos, your history and your agents, homegrown or off-the-shelf. It adapts to your setup; you don’t change your workflow.