Private LLM copilots
Internal assistants grounded on your policies, product specs, and customer data — deployed inside your network, never to a vendor API.
Banking, insurance & asset management
AI that survives the compliance review.
SOC 2 and GLBA-aware engineering for banks, insurers, and asset managers. We ship LLMs, fraud systems, and analytics that keep customer data inside your perimeter and produce outputs your risk team can audit.
What we build for finance
Fraud & anomaly detection
Real-time transaction scoring using graph and sequence models. Explainable outputs for Reg-B / fair-lending compliance.
Document AI for underwriting
Extract structured data from loan applications, KYC packets, and insurance claims. Every extraction is traceable to its source page.
Why regulated finance needs a different AI stack
Model explainability isn’t a "nice to have" in banking — it’s a regulatory requirement. A model output that affects credit, pricing, or fraud determination needs a defensible paper trail. We design every model pipeline with grounding, citation, and confidence scoring as first-class outputs, not afterthoughts.
For LLMs specifically, the hosted-API model is fundamentally incompatible with most financial-services data agreements. Our default deployment is your own infrastructure — private cloud or on-prem — with model weights, vector indices, and logs all inside your control plane.
Compliance posture
- SOC 2 Type II-ready architecture from day one (encryption, access controls, audit logs)
- GLBA-aware data handling for customer financial information
- Segregation of duties built into MLOps workflows
- Model evaluation reports suitable for model-risk-management review