25–35% of engineering capacity disappears into maintenance. Aevon measures exactly what share AI can absorb — and returns that capacity to the roadmap.
Every engineering budget is now defended against an AI question. Everyone suspects AI could absorb a meaningful share of maintenance. Almost nobody can say which share, with a number their CFO will accept — so a pilot gets run, a demo gets shown, and the room goes quiet.
We answer the question the pilot could not.
An embedded engineer works inside your team — measuring, week by week, what AI would actually have resolved.
The CIO, CFO, CPO, and board are not asking the same thing. The same evidence answers all four — without contradiction.
Our team has built and shipped enterprise software at Microsoft, Salesforce, Oracle, and KKR-backed companies — and co-founded a B2B platform through to exit. We know what production-ready means when it's your name on it.
An assessment that can only conclude yes is not an assessment. We would rather deliver an honest no.
The value is measurement discipline that holds up when a sceptical CTO pulls on it.
Evidence, models, documentation, blueprint. No lock-in, no black boxes.
We take a limited number of engagements so each is led by the people who designed the method.
No SDR layer. The first call is with the person who will lead your engagement.