Tools you ownSurface area
Custom models.
We fine-tune and train with reinforcement learning on your data and your agents' traces, for the tasks general models get wrong.
Your own stack.
We set up the infrastructure on-premise, on local machines or in your cloud, and pick models by testing them on your tasks for accuracy, speed and cost.
Harnesses for raw agents.
We wrap each agent in the tools it's allowed to use, the rules it can't break, validation on everything it writes and approval before anything leaves the company. That's what makes an agent safe to run real operations.
Traces and evals.
We log every agent run so it can be replayed, and build test suites that catch regressions before a model or prompt change goes live.
In practice
Off-the-shelf tools can't transcribe songs sung in regional languages. They miss words, and their timing drifts the longer a song runs. For a music label we built a lyric engine that gets both right: every line found, and timed within a tenth of a second of a human editor.
