AI agents that run in your infrastructure.

You send a week of agent transcripts and the billing that goes with them. I send back a written report: where the tokens go, which sessions are responsible, what to cut, and what the cut is worth per month.

I ran this on my own usage first. 1.48 billion tokens in seven days, 99.6 percent of it input. One session was reading four novels' worth of context to write a single reply, every turn, for five days. Fixing it took the daily cost from $600 to $125 on the same workload.

The tooling I built for it is open source, so you can check the method before you pay for it.

Deployed to your AWS, on your own Claude or Codex subscription. Nothing routes through me and nothing routes through a vendor.

Credentials sit behind the tool layer. The model holds a tool name and never a key, so a prompt injection cannot turn into a breach.

Work comes back as a pull request. You review a diff instead of discovering an action that already happened.

This is Citio. It is open source, it is running in production, and you can read the whole design before you hire anyone.

Capped days each month. I maintain the deployment, audit the spend, and add capabilities as the models change underneath you.

Model releases break assumptions every few months. Someone has to own that, and for most teams it is not worth a headcount yet.