Priced like a system, not a seat.
You're not buying logins. You're buying a decision engine pointed at your problem — grounded in your data and the rules you answer to, and owned by you. Three ways to start, scoped to the work rather than the headcount.
Pilot
The shortest path from “could AI do this?” to a verdict your experts will sign.
- One framework, one artifact type — end to end
- Your knowledge base + the external rulebook, assembled
- A working decision on real documents: evidence + confidence
- An honest read on time-to-v1 and the long pole
Build
Knowledge base, process, and custom software — in production, owned by you.
- Everything in Pilot, across your real workflow
- Process & criteria onboarding with your experts
- Custom product built around your problem
- Deterministic QA where the numbers have to be right
- Expert overrides that recalculate and propagate
- Runs on your stack — your data stays inside your boundary
Platform
Your own decision engine across teams — kept current as models and rules change.
- Everything in Build, across multiple frameworks
- Model-agnostic — Claude, GPT, Gemini, open-source, swappable
- Constantly upgraded as models advance & regulations change
- Source-transparent, version-correct — always current
- Priority support and a roadmap that tracks your field
Every engagement is scoped to your problem — these are starting points, not a menu. Tell us the documents and the rulebook.
Whichever tier you start at, the engine is portable.
Model-agnostic, source-transparent, and always current — by design. Not locked to a model, a vendor, or a frozen snapshot of the world.
Works with any LLM
The model is configuration, not architecture. Combine frontier and open models, swap them as better ones ship — Claude, GPT, Gemini, or open source. No lock-in.
Runs on your stack
Your cloud or your intranet. Your data stays inside your boundary — the engine comes to the data, not the other way around.
Grounded in public truth
Built on public sources, laws, codes, and the standards your field answers to — version-correct, jurisdiction-aware, and cited so every call can be checked.
Constantly upgraded
As models advance and regulations change, the engine and its knowledge base update with them. You're always on the latest — not last year's snapshot.
We don't hand you a tool. We build the system around your problem.
The engine is the platform. The engagement is how we point it at your world — your data, your regulatory environment, your process. Every tier follows the same three steps; they differ in scope, not in kind.
Build your knowledge base
We assemble your institutional data and the regulatory environment you operate in — laws, codes, standards, rubrics — into one grounded, version-correct source of truth.
Onboard your process & criteria
We sit with your experts to capture how you actually work — your workflow, your evaluation criteria, your edge cases — so the engine reasons the way your best people do.
Ship custom software
We build the product and the processes around it — tuned to your problem, running in production, owned by you and upgraded as your field changes.
The engine is the platform; the engagement is how we point it at your world. One partner, from knowledge base to working software.
Before you ask, the short answers.
Because the value isn't seats — it's a system pointed at your problem. You're buying a decision engine that reads your hardest documents and produces verdicts your experts will sign, not logins. We scope to the work, not the headcount.
Yes. The product, the processes, and the knowledge base are yours — running on your stack, inside your boundary. The engine is the platform; the engagement is how we point it at your world.
Whichever is best for the job. The model is configuration, not architecture — Claude, GPT, Gemini, and open-source models sit under the engine, and we swap them as better ones ship. No lock-in, no competing with your existing AI.
A pilot proves a single framework fast — often weeks, not quarters. We name the long pole on time-to-v1 up front, so you know the path before you commit to the full build.
Tell us the documents and the rulebook.
We'll scope the right way to start.
A pilot proves a single framework fast — the shortest path from “could AI do this?” to a verdict your experts will sign.