Ai Cell designs, trains and runs the systems that let a company think faster than its market. Research-grade models, agent infrastructure, and the interfaces people actually use — built by one small team that stays on the problem.
One brain, half grown and half built. The same body of work sits in both halves — loose on the left, filed in rows and columns on the right. Retrieving an item from a heap means searching the heap. Retrieving it from an index does not. That difference is the whole case for putting a model in the loop.
Four practices, one team. Every engagement draws on all of them, because a model that nobody can operate is not a result.
We read the literature, then ship only the parts that survive contact with your data. Fine-tuning, distillation, retrieval, and the evaluation harness that proves it moved.
Tool-using agents wired into the systems your team already runs, with the guardrails, audit trail and human checkpoints that make them safe to leave running.
Pipelines, labelling, vector stores and serving. We measure cost per thousand calls and p95 latency from day one, then keep both falling.
The surface decides whether anyone trusts the output. We design and build it — the review queue, the confidence display, the undo — as part of the system, not after it.
Each stage ends in something you can keep — a document, a running service, a dashboard — whether or not you continue to the next.
Two weeks inside the work. We map where judgement is slow or expensive and pick the one place a model changes the number.
Ends in: scoped briefA working system on your own records, measured against the humans doing it today. If it does not beat the baseline, we say so.
Ends in: eval reportInto production behind your auth, your logging and your rollback. Shipped to a small group first, widened once the metrics hold.
Ends in: live serviceDrift monitoring, cost tracking and retraining on a schedule — run by us, or handed to your team with the runbook.
Ends in: handover or retaineraicelliraq@gmail.com