Regulated Finance
Evidence that survives the next exam
Banks, credit unions, wealth, payments, lending, and capital-markets infrastructure.
Industries we have delivered in
AI value and risk change by the work you run.
Finance is the ratified ICP and where we go deepest: private equity, banks and capital markets, fintech, asset and wealth, real estate, and insurance. The broader delivery record spans education, manufacturing, food, agritech, cybersecurity, FP&A, and AI-native product work, expressed qualitatively and anonymized.
Industries9
Evidencelive
Read2 wk
AI value and control, mapped to this market.
Every claim in the read traces back to source evidence, ownership, and the workflow decision it supports.
Valuefund next
Riskcontain now
Fluencytrain where work changed
01
Private Equity
Portfolio-wide AI value capture and control coverage.
Open detail
02
Regulated Finance
Banks, credit unions, wealth, payments, lending, and capital-markets infrastructure.
Open detail
03
Banks & Capital Markets
Regulator-defensible evidence under model-risk pressure.
Open detail
04
Fintech
Ship reliable AI without losing enterprise buyers.
Open detail
05
Asset & Wealth
Advisor, ops, and research workflows with evidence attached.
Open detail
06
Real Estate
AI-driven NOI, leasing, valuation, and asset-model proof.
Open detail
07
Insurance
Underwriting and claims AI that can be defended.
Open detail
08
Education
Student, faculty, and operational AI workflows with measurable trust.
Open detail
09
Manufacturing
Plant, quality, procurement, and service workflows made reliable.
Open detail
Sector-specific proof patterns, not a second chooser.
Private Equity
A value and risk read the IC can underwrite
AI
Portfolio-wide AI activity turned into fundable workflows and contained exposure.
Real Estate
NOI, leasing, valuation, and reporting proof
AI
Data
Emails
Files
People
Data
Emails
Files
People
AI outputs tied to source records and economics an operator can defend.
Fintech
Reliable AI that clears enterprise buyers
Feature behavior, evals, and procurement evidence on one pipeline.
Insurance
Defensible underwriting and claims decisions
Controls and evidence for consequential outputs before they become the record.
Asset & Wealth
Advisor, ops, and research workflows
Recommendations, research, and client-facing AI with source-linked proof.
Education
Learning and operations AI with trust evidence
Index Knowledge
Student, faculty, and institutional workflows measured before scale.
Manufacturing
Plant, quality, procurement, and service AI
Operational workflows instrumented for reliability, exception handling, and value.
Evidence trail
The number only matters when the work beside it is visible.
Each proof artifact now shows what changed, what TrustEvals installed, what evidence was captured, and where the reader can inspect the case.
Evidence cases
AI-native finance SaaS
A release gate the product team and customers could inspect.
95%stated accuracy after the deploy-gate work
Before
~60% FP&A accuracy and repeated double-checking before release.
01Golden set
02Regression DAG
03Reviewer checks
04Release decision
Result
95% stated accuracy, about 90% measured, with 144% NRR provenance kept beside the claim.
- 90+ scenarios
- deterministic SQL fast paths
- reviewer-agent checks
- claim labels kept explicit
AI-native finance SaaS / FP&A95% stated accuracy, ~90% measured, 144% NRRFinance SaaS false positives20% fewer false positives, rollout to 100+ customersUS commercial real estate$20M modeled 10-yr NOI/NPVTrust harnessnew frameworks map on top, not a re-plumbProof disciplineclaims stay tied to engagement evidence
From uncertain FP&A accuracy to a deploy gate our customers could review.
CTO, AI-native finance SaaSTrustable, reliable AI in production
Start with the AI work that moves the number. Keep the proof built in.
Start with Strategy, Transformation, or Fluency; use Quick Audit when the first need is an independent read on what is already running.