The assessment answers the question. The practice is what you build once the answer is yes. Aevon can extend from measurement into the design and operation of the function that runs AI-assisted maintenance on an ongoing basis.
Most AI assessments end with a slide deck and a recommendation. Ours end with a blueprint. For clients who want to go further, we can build and operate the function the blueprint describes — the team, the tooling, the governance, and the SLA that runs AI-assisted maintenance on an ongoing basis.
This is not a consulting extension. It is a different engagement model: we own the outcome, not the hours.
We design the AI-assisted maintenance function from the ground up — tooling selection, integration with your existing CI/CD, governance model, escalation paths, and the SLA structure for each issue class.
We operate the function under a clear SLA. Every automated change is gated, reviewed, and audit-ready. We report on capacity released monthly, benchmarked against the baseline from the assessment.
The AI landscape moves fast. We manage model updates, retrain on your evolving codebase, and expand the automation scope as new issue classes become addressable. The maintenance tax stays down as the codebase grows.
There is no black-box automation in this model. Every automated change is proposed, reviewed by an engineer, and approved before it is merged. The review time is the saving — not the removal of human judgment.
This structure is deliberate. It means the function is clean for diligence and exit from day one. It means engineers stay engaged with the codebase. And it means the system degrades gracefully — if a model update produces lower-quality output, the review layer catches it before it reaches production.
The practice engagement is only available to clients who have completed the assessment. The evidence comes first.
Start with the assessment →