FinTech Platform Modernization for Enterprise Compliance
A financial technology company needed to meet enterprise banking procurement requirements — SOX-aligned controls, auditability, and data residency — before its AI features could be adopted by regulated customers.
- App Factory
- Delivery Model
- By default
- Governance
- Customer-controlled
- Residency
The operational problem
The blocker for AI features in regulated procurement is rarely capability — it is the evidence package. Buyers ask who can access what, where data lives, how model changes are reviewed, and how it is all proven. Platforms that generate that evidence as a side effect of running get through review; platforms that assemble it manually do not.
What Enfuse built
- Governed release pipeline for AI application changes
- Policy, access, and audit enforced at the runtime layer rather than per app
- Application templates with governance controls pre-wired
- Evidence export aligned to the customer's control framework
Architecture
- Runtime — policy, identity, audit, and evaluation shared across applications
- Factory — templates, scaffolding, and release pipeline for new AI apps
- Evidence — continuous control reporting drawn from runtime telemetry
Hardware and software
- Sovereign Runtime + App Factory
- Customer-controlled infrastructure (on-prem or dedicated tenancy)
- Existing identity, ticketing, and GRC tooling
Deployment environment
Customer-controlled infrastructure with no shared multi-tenant inference.
Results
- Repeatable path from prototype to governed production application
- Control evidence produced continuously from runtime telemetry
Reference architecture. Describes the delivery pattern; commercial outcomes are not published.
Discuss this pattern against your environment
Bring your constraints — sensors, security boundary, latency budget — and we will tell you what is realistic.