Services / Custom AI systems
Purpose-built AI systems
General-purpose chat tools stop being useful exactly where the stakes start: when outputs must be sourced, evaluated, and defensible. We build systems for that territory.
What kind of systems?
- Agentic deep-research pipelines — multi-pass research over public and internal sources, producing drafts where every claim carries a citation and a confidence grade, and where missing evidence becomes a flagged gap instead of a guess.
- Document-intensive workflow tools — systems that read, cross-reference, and draft against large document sets (filings, contracts, technical reports) with human review built into the workflow, not bolted on.
- Evaluation harnesses — the part most AI projects skip: measurable criteria for whether the system's outputs are good, run continuously, so "it works" is a number you can defend.
What makes ours different?
A design rule we apply everywhere: the model asserts; deterministic code decides. Identifiers, source classification, confidence scoring, and document assembly live in reviewable code — not in a prompt. That's how we build systems where an ungrounded output structurally cannot be emitted, rather than merely being discouraged.
See it applied in our case study: agentic industry research for a national competition regulator.
Where does it run?
In your infrastructure, under your accounts, in repositories you own from day one. We deploy to your cloud (or a host you choose), wire up observability, and hand off documentation and runbooks — the system keeps working when the engagement ends.