AI-native software engineering
Anyone can catch it now — models made the impossible demo cheap. Shipping is still the work: software that holds up under real users, real data, real load. Zedrevo builds AI agents and the systems around them, and stays until they carry weight in production.
Zedrevo was never a pre-AI company adding new tools. The firm's own operating system was designed after AI existed — and that is a checkable difference, not a slogan.
Most projects treat it as the finish line. A demo proves an idea; production proves a system — under real users, real data, and the failure modes nobody demos. That second proof is what we sell.
We build AI agents under graduated autonomy: approval gates on everything at first, autonomy expanded only where the evaluation record earns it.
For workflows where a working agent changes the economics of a business function.
Agent systemsOn-prem and in-VPC deployment of open-weight and frontier models. Your data stays inside your perimeter; there is no traffic we can see.
For organizations where data residency and provider independence are contractual requirements.
Private inferenceDeterministic systems — the kind you would scope at two quarters — delivered in weeks, because our pipeline was designed after AI existed.
For teams that need real software sooner than a traditional vendor can schedule a kickoff.
Software, acceleratedA short, paid engagement answering two questions: where would AI produce the most value in your operation, and what has to be true for the risk to be acceptable.
For leadership that wants a defensible answer before committing a budget.
Value mappingLight is predictable — it arrives the same way, every time. That's the speed worth engineering for: not a heroic sprint, a pipeline that produces the same result every run.
We map the workflow, the data, and the risk. Paid, fixed fee, and useful even if it ends here.
A working system on a real workload with real users — designed from the start to reach production, or to fail honestly and early.
The system carries real load. Autonomy expands only as the evaluation record earns it; every gate we relax is a decision with evidence attached.
Your team operates it without us. Handover is part of the build, not a renegotiation.
Earned in stages, on evidence. Models make mistakes — we assume it, measure it, and build the system that catches it before your customer does: approval gates on everything at first, autonomy expanded only where the evaluation record earns it.
The full list of refusals is on the how-we-work page. Every one is a policy, not a pose.
The last letter
We’ll tell you, plainly, whether we can finish it — and what it would take. A person replies within two working days.
