Industries
Financial services
Model risk management, supervisory reconstruction, and data that cannot leave the estate, with deadlines set by someone else.
What makes this sector different
Reconstruction, years later
A supervisory sample can arrive long after the decision. If answering it requires archaeology across systems, the system was built wrong.
Model risk governance
Existing model risk frameworks were written for statistical models and are being stretched over language systems. The documentation expectations transfer; the validation methods often do not.
Data residency and third parties
Outsourcing and third-party risk regimes make a hosted API a governance question before it is a technical one.
Remediation deadlines
Programmes with fixed regulatory end dates cannot absorb a six-month platform detour.
Workloads that come up
- Document-heavy remediation and file review
- KYC and onboarding evidence assembly
- Complaints triage and root-cause clustering
- Surveillance and alert reduction
- Policy and procedure question answering for front-line staff
- Regulatory change impact mapping
Frameworks in play
Two patterns we deploy here
Declared-graph case review with escalation
Structured extraction and consistency checking, with anything ambiguous routed to a named reviewer and every transition recorded in a framework-independent trace.
Grounded internal policy assistant
Retrieval over policy and procedure with entitlement filtering at query time, citation of the governing source, and suppression of uncited answers.
Start with the constraint.
Most of these projects are shaped by what you cannot do rather than what you want. Data that cannot leave the estate, a model you cannot host with a third party, a decision somebody has to justify to a regulator. Tell us yours and we will say honestly whether we can work inside it.