Attribution and reconciliation
Break detection with a recommended adjustment and a written explanation, so sign-off becomes review rather than reconstruction.
FINANCIAL SERVICES
AI for financial services
Banks run on review queues, reconciliations, and sign-offs that a trained person performs the same way a thousand times. That work is carryable by agents, if every decision keeps its evidence.
What makes this hard
- 01Controls staff spend the month closing the books rather than explaining them.
- 02Fraud and compliance review volume grows faster than headcount can follow.
- 03The reason a decision was made lives in a person's memory, not a record.
Where agents earn their seat
Governed review queues
Screening work turned into an audited pipeline where a reviewer gets an evidence pack and a one-click decision.
Document and trade operations
Extraction and drafting across the paperwork that moves money, with a person approving before anything commits.
The constraint we design around
Everything must be reconstructable. Regulators ask why, not whether, so systems record their inputs, their reasoning, the human who approved, and the path to reverse it. Data tiering and residency get decided before the first model call, not after.
