Most banks have a pilot.
Few have it in production.
We put senior engineers inside regional banks, wealth managers, and specialty insurers. They work on your data, on your stack, and they answer for what ships. We stay until it runs in production, then hand it to your people.
Ninety minutes, one real workflow. You leave with the candidate architecture and the governance outline. We have not pitched you anything yet.
The hard part was never the model.
Your teams are already using it. Your budget already went up. What almost no one can show is a single dollar it returned. The blockers are not the models. They are fragmented data, legacy cores, vendor systems that decide for you, and the governance that real deployment demands.
We embed, we build,
and we stay on the hook.
Strategy firms leave after the deck. Core vendors lock the intelligence to their platform. We are neither. The engineer who designed it is the one who answers when it breaks at nine in the morning.
On your floor
The same engineers from intake through handoff, on site, on your systems. No junior relay, no offshore handoff.
Working software
We ship the workflow itself, not a recommendation to build it: the integrations, the evaluations, the controls.
Documented for the exam
Every system is testable, explainable, and documented to the standard your examiner already applies.
You own it
Your people own what we build. We leave the reusable assets behind, so the next one costs less.
Fixed scope, fixed fee, no open ended retainers. A first production workflow typically runs eight to twelve weeks, with the price quoted before any access.
A pilot is a demo with the risk turned off.
Production is the part your examiner signs.
How an engagement actually gets made.
A named person on our team owns every claim, every build, and every number that reaches you. We use our own tooling to move faster, and a human reviews and signs everything before it leaves.
Intake
Reads your context: documents, data, the stack as it really is.Output / a current state map
Diagnose
Pressure tests the brief against your data, so we solve the problem that is actually costing you.Output / the prioritized problem
Map
Charts the current process and the path forward.Output / a process map
Architect
Designs the system and the build plan.Output / a target architecture and a risk register
Build
Ships the production system into your environment.Output / working software
Integrate
Connects your systems and vendors, around the core.Output / live integrations
Ground
Every claim is checked against a live source and cited, and the check is logged.Output / a citation log
Measure
Tracks adoption, evaluation scores, and the dollar outcome we agreed to in week one.Output / an outcome report
A young firm, with the parts you can write into a contract.
We will not show you logos we have not earned. We will show you exactly how the work runs, and put it in writing.
A first production workflow in eight to twelve weeks.
A fixed price quoted before week one, not a retainer that grows.
A model risk file your examiner can open: lineage, evals, fair lending tests, a citation log.
Every commitment above goes into the engagement agreement, with audit rights and a right to terminate. We are taking on our first design partners at founder led pricing, and references follow once we have earned them.
Built for mid market financial services.
We chose this segment deliberately. It carries the same regulatory weight as the largest institutions, with a fraction of the bench to meet it.
Regional and community banks
Get one fraud or lending workflow past the pilot and into the core. Anti money laundering, credit decisioning, deposit operations, and the data foundation underneath.
Wealth and asset managers
Govern the shadow AI already inside your firm, then go past the meeting notetaker: adviser productivity, client reporting, and surveillance, with a human in the loop.
Specialty insurers and MGAs
Submission intake and triage, underwriting data, claims processing, and fraud, with appetite discipline and audit trails intact, on the policy systems you already run.
Fintechs
Move at fintech speed with controls your sponsor bank will not balk at. We build the AI surface and the governance your partners and regulators expect before they say yes.
We build inside the regime you already answer to.
SR 11-7 model risk management, the GLBA Safeguards Rule, ECOA and fair lending, the NIST AI Risk Management Framework, and the NAIC Model Bulletin on AI all still apply the day your model goes live. We build to them from the first commit. We hold no platform license to defend, so we pick the right model and tools for your problem, not ours.
Your data never leaves your environment or a cloud tenant you approve. We do not train models on your data, and nothing goes to a model provider you have not approved. We sign a mutual nondisclosure agreement before any system access, complete your vendor security review, and grant you audit rights and a right to terminate with artifacts returned, in writing.
- AI recommends. Accountable humans decide. Human oversight sits in every consequential workflow.
- Explainable by default. When a model touches a credit decision, it states the specific reasons an adverse action notice requires.
- Tested for bias across the lifecycle. Fair lending work, documented, not assumed.
- Built to SOC 2 and GLBA controls. We welcome your security review and will sign your audit rights in writing.
Senior judgment from inside finance, paired with hands on engineering.
Clairvance was built in Chicago by an operator who spent years inside a global bank and has shipped real systems. We chose the mid market deliberately: the institutions the largest firms will not staff with their best people, and the ones most exposed to the distance between a pilot and a governed, production system.
Chicago, Illinois
Bring us the workflow
costing you the most.
Give us one real workflow and ninety minutes. You leave with a candidate architecture and a governance outline you can take straight to your risk committee, whether or not you ever hire us.