AI made code cheap. It did not make systems healthy.
pachx combines deterministic code analysis with engineer‑steered AI agents to keep software tested, maintainable, updated, and safe to change.
pachx first maps your codebase: languages, frameworks, endpoints, dependencies, IO boundaries, tests, and the paths through which change can spread.
Before an agent changes code, pachx builds the context it needs to act safely.
Agents are powerful, but they are not disciplined by default. pachx gives them bounded tasks, deterministic context, tests, policies, and verification loops. The engineer decides the direction. The agent does the work. The system checks the evidence.
Most tools tell you a new dependency version exists.
pachx asks a harder question: is your system ready for that update?
It finds where the dependency is used, checks the tests around those paths, understands the upstream changes, improves the safety net where needed, applies the update, and verifies the result.
If the evidence is not strong enough, pachx does not pretend. It tells you what is missing.
Every change has a blast radius: callers, consumers, endpoints, tests, dependencies, configuration, and behaviours that may be affected.
pachx maps that radius before the change is made, then verifies the paths that matter after it lands.
You see the risk before the release, not after a customer finds it.
Healthy software is not only covered by tests. It is understandable, observable, secure, updated, and predictable. pachx looks across the system: endpoints, inputs, API consumers, dependency risk, CI configuration, cloud configuration, security exposure, performance risks, and architectural drift. The goal is not to create new features — the goal is to keep the system fit to change.
Coverage where it matters: the paths change actually touches.
Versions, vulnerabilities, and readiness to upgrade.
Surface area, inputs, contracts, and consumers downstream.
Exposure of secrets, IO boundaries, and risky patterns.
Pipelines that report truth, not just a green checkmark.
Infra, permissions, and runtime posture in the same view.
Hot paths, regressions, and the cost of every change.
Where the system is moving away from its own intent.
pachx is not here to replace engineering judgement. It keeps agents inside clear rails: small tasks, explicit policies, repeatable checks, tests, rollback paths, and human approval where it matters. Quality should not depend on whether an agent behaved well this time — it should come from a repeatable system.
pachx helps teams maintain the health of the systems they depend on, even as AI increases the speed and volume of change.