About I‑Ops
The layer that checks what AI workers actually did, rather than what they said.
I‑Ops Operations Intelligence LLC builds the layer that checks what AI workers actually did. Not whether an action was permitted, and not whether a command exited zero, but whether the thing that was asked for became true — checked by code that is not the worker that did the work.
The reason that distinction matters is that it is the one every other layer stops short of. A policy gateway decides whether an action may run. An observability tool records that it ran. Neither answers whether the intended outcome holds afterwards, and an agent asked to confirm its own work will tell you that it does. That is not dishonesty in the model; it is a structural problem with asking any worker to mark its own homework, and it does not go away as models improve.
So the guarantees are computed by ordinary code, from artifacts that already exist — the session transcript, the test run, the git history, the import graph, the CODEOWNERS file. Nothing is predicted. Where a thing cannot be determined, the answer says so rather than guessing, because an unknown reported as a pass is worse than no check at all.
Several of those layers are open source under Apache‑2.0, run entirely on your machine, need no account and no network, and come out in one step. The tools are here, the source is at github.com/i‑ops‑hq, and the packages are on PyPI and npm. A signed macOS application is in private testing.
The company is one person: Ashwinth Reddy, founder, and the LLC is registered in Delaware. Public record of the work is on GitHub and LinkedIn.