A claims desk that closes its own loop
A permissioned agent reads intake documents, drafts adjudication, and escalates anything below a confidence floor. Every action is traced and replayable.
Agentic AI
Multi-step orchestration, tool use, permissioned actions and human checkpoints — built to run unattended and be audited afterwards.
Agentic systems fail in ways ordinary software does not: they fail probabilistically, mid-plan, and often silently. We engineer for that. Every agent we build is a graph of explicit steps with typed inputs and outputs, not an open-ended loop hoping a prompt holds.
Tools run inside sandboxes with least-privilege scopes. Actions that change state require a permission the operator granted in advance, and anything below a confidence floor escalates to a human rather than proceeding. Every step is traced, so a run can be replayed exactly as it happened weeks later.
Before an agent reaches production it has to clear an evaluation set built from your real cases. We report the score, the failures, and what we changed — because an agent without an eval is an anecdote.
What we build under this capability now, with the architecture and the evaluation it is held to. Figures are illustrative until a client approves the real ones.
A permissioned agent reads intake documents, drafts adjudication, and escalates anything below a confidence floor. Every action is traced and replayable.
Retrieval, extraction, classification and fine-tuning on proprietary corpora — measured against a benchmark you can defend.
Contracts, indexers and wallet-grade infrastructure with deterministic test suites.
Market-data ingestion, execution pipes and risk tooling. Engineering only — never advice.
Interfaces, billing, permissions and the platform that keeps intelligence shippable.
Product design, design systems and prototyping — so the intelligence underneath is usable, and the product looks the part.
Tell us the system you can't get built. We come back with a short, paid discovery — a clear plan and a fixed first milestone — usually within two working days.
A working session to map the problem and define what "good" is measured against.
Architecture, milestones and a fixed first deliverable — yours to keep, either way.
Embedded with your team or as a dedicated pod, shipping with traces, evals and docs.