Agentic AI systems that finish the work

An agent is worth building when a task is repetitive, high in volume, and currently done by a person clicking through an interface. We build the ones that finish: the agent reads your systems, decides, acts, and leaves a record of what it did.

Most agent projects fail in the same place. The demo works, then production adds retries, partial failures, and a tool that returns nothing the agent can check itself against. We design for that from the first week.

What an agent has to survive in production

Three layers of a working agent retry independently: the model, the tool client, and the network underneath both. Only the model call is safe to repeat. Every write needs a read in front of it, or the agent books the same room twice and no log tells you which attempt was the real one.

We built OFFSET, which files Greek short-term-rental declarations on the ΑΑΔΕ portal by driving the interface, because the portal exposes no API at all. There is nothing to reconcile against except the portal's own submission listing, so the design reads that listing back before it continues.

Where agents earn their cost

• Work that arrives as messages: guest, customer and supplier threads spread across channels.
• Work that arrives as documents: invoices, receipts, statements and forms needing extraction and validation.
• Portals with no API, where the only interface is a browser and somebody who knows the click order.
• Reconciliation between two systems that disagree, run on a schedule instead of when a person remembers.

How we build them

Every agent ships with the unglamorous parts attached: an eval set that runs on each change, guardrails on every write, and monitoring that reports what the agent did rather than that it was up. You get the repository.