AI for fintech that ships in your product

Fintech is software-native, so the AI usually has to ship inside your product, not sit beside it. That changes the engineering brief: API-first, latency-sensitive, multi-tenant, and built to your security bar. The most common asks are embeddable features — a financial assistant in-app, smart categorization, or a conversational interface over a user’s transactions — that have to feel native and never hallucinate a balance.

Risk and fraud are where ML earns its place. Onboarding risk scoring, transaction anomaly detection, and document verification for KYC are pattern problems where a tuned model plus an LLM for the reasoning and explanation layer beats rules alone. We build these to be explainable, because in fintech a black-box decline is a support ticket and a regulatory question at once.

Operations and support scale with the business: a grounded support agent over your product docs and a user’s account state, dispute handling, and reconciliation copilots that read statements and flag mismatches. We design for the fintech reality — sub-second responses, PCI-aware boundaries, audit trails, and data isolation per tenant — and we’ve learned it operating our own products in production, not from a slide deck.