Systems
We build what does not exist off the shelf: transactional platforms, internal systems, integrations between things that were never meant to speak, and AI components with a deterministic layer underneath them.
You are probably reading this because:
The off-the-shelf product covers 70% and the remaining 30% is where your margin lives.
You have an AI prototype that demos well and cannot be trusted with a real order.
Three vendors each built a piece and no one owns the seam between them.
The system works, but only one person understands it.
- 01
Product and platform engineering
Full delivery from domain model to production: backend, data layer, interfaces, and the operational tooling the team needs to run it without us.
- 02
AI systems with a deterministic core
Language models are useful and unreliable in the same breath. We constrain them with a deterministic layer that encodes the rules of the domain, so the probabilistic part can be wrong without the system being wrong.
- 03
Integration work
Payment gateways, ERP, accounting, logistics, messaging, government portals. The unglamorous half of every platform, and the half that decides whether the other half is usable.
- 04
Instrumentation from day one
A system that cannot be observed cannot be improved. Logging, tracing and the metrics that matter to the business are part of the build, not a later ticket.
- 01
Working software in production, released in stages
- 02
Source, infrastructure and deployment owned by you from the first commit
- 03
Documentation aimed at the next engineer rather than at the invoice
- 04
A handover that ends with your team shipping without us
Invariant
A probabilistic component is only safe inside a deterministic boundary.
- What stack do you work in?
- Python and TypeScript for most delivery, PostgreSQL as the default system of record, Kafka where events genuinely need decoupling, and the major model providers for AI components. The stack follows the problem; we do not have one to sell you.
- Can you take over a codebase someone else wrote?
- Yes, and it is a large part of what we do. It starts with an audit, because inheriting a system without understanding its model is how the second rewrite gets commissioned.
- Do you build AI agents?
- We build systems that use models where a model is the right tool. The engineering question is never the model — it is what the system is allowed to do when the model is confidently wrong.