Market-data plumbing that stops guessing
Normalised multi-venue ingestion with deterministic replay, so teams can reproduce any minute of the day. Infrastructure only — no strategy, no advice, no return claims.
Reference architecture · Agentic AI
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.
01Agentic AI
The problem
Claims intake arrived as a mix of scanned PDFs, email threads and structured forms. The team could not scale review headcount fast enough, but they also could not accept an opaque model making payout decisions.
02Agentic AI
What we built
We built a permissioned agent as an explicit graph: extract, normalise, check policy, draft adjudication, and route. Each step has typed contracts and its own evaluation. Anything below the confidence floor escalates to a human with the evidence attached rather than being auto-approved.
03Agentic AI
What it proved
Every run writes a trace that can be replayed exactly, which is what made the system auditable enough to deploy.
→What it is held to — illustrative figures
The numbers
Each figure is the measurement the system is held to. These are placeholders from the design comps until client-approved numbers replace them.
Architecture
Measured continuously; a regression here fails the build.
P95 latency
Measured continuously; a regression here fails the build.
Eval coverage
Measured continuously; a regression here fails the build.
This reference architecture sits under our agentic ai capability. Its figures are illustrative until a client approves the real ones.
↺
Other reference architectures
A custom pipeline for a 40-year archive
OCR repair, entity resolution and a domain fine-tune turned an unsearchable corpus into a retrieval layer with a defensible accuracy benchmark.
Settlement rails with deterministic tests
Contracts and an indexer with a full replay suite, so every state transition is reproducible before it ever reaches mainnet.
→Start here
Let's build
the impossible.
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.
01
Discovery
A working session to map the problem and define what "good" is measured against.
02
The plan
Architecture, milestones and a fixed first deliverable — yours to keep, either way.
03
We build
Embedded with your team or as a dedicated pod, shipping with traces, evals and docs.