HomeServicesPortfolioAboutContactBlogCareers
For Fintech Teams

AI agents and fraud models for fintech, shipped to production.

Real-time risk scoring, support and ops agents, and LLM integrations, built for regulated financial workflows, where every decision needs to be explainable months later, not just fast in the moment.

What we build for fintech
Fraud & Risk Scoring
Real-time models blending a gradient-boosted baseline with an LLM reasoning layer over transaction and device signals.
Support & Ops Agents
LLM agents with function calling over your internal systems, with confidence-based escalation to humans.
Backend Engineering
APIs, data pipelines, and infrastructure that hold up under real production traffic.
AI Integrations
LLM agents, RAG search, and automation grounded in your real data, with no hallucinated capability.
Proof, not promises
Fintech

−40% false positives on real-time fraud scoring

An LLM-augmented risk model scoring transactions in real time to catch fraud without blocking good customers.

−40%
False positives
+22%
Fraud caught
<200ms
Scoring latency
Read the case study →Architecture pipeline →
Built into your stack

AI, payments, and integrations for fintech products

The model is rarely the hard part in fintech. The hard part is wiring it into payment flows, event pipelines, and review processes that already exist, without slowing approvals or breaking the audit trail.

Fraud scoring inside the payment flow

Our fraud model scores each transaction in under 200 ms, so it can sit inline before approval instead of reviewing after the fact.
Read the architecture →

Voice agents on your loan systems

A speech-to-speech assistant that qualifies applicants and checks application status through the same APIs as our support agents. It took 35% of the load off a lender's call center.
Voice AI case study →

Payments and subscription billing

Stripe, Chargebee, and Orb integrations with verified, idempotent webhooks, so billing state and your own records agree.
Payments and subscriptions →

Event pipelines and APIs

Kafka for high-volume scoring events, RabbitMQ and Celery for background work, and clients for the third-party APIs your product depends on.
API and SDK integration →
Further reading
How Real-Time Fraud Scoring Systems Are ArchitectedHow an Online Feature Store Works for Real-Time Fraud ScoringRules Engine vs LLM Fraud Scoring: What Actually ChangesWhat Counts as Explainable AI in Fraud Detection?How a Low-Latency Voice AI Assistant Is ArchitectedFunction Calling on a Live Call: Keeping Lookups Under the Conversation Budget
FAQ
How do you handle explainability for compliance?

Every scoring decision is built to be reconstructable after the fact, for a compliance reviewer or a disputes team, not just fast in the moment.

How long is a typical engagement?

4–10 weeks for a first build, ongoing retainers after.

Do you work with in-house risk and data teams?

Yes. We embed alongside existing engineering and data teams, not around them.

Can you integrate our payment or billing provider?

We have integrated Stripe, Chargebee, and Orb, including webhook handling and subscription state in your own database.

How do you price fintech work?

Hourly or as a monthly block of hours. We do not quote a fixed price per project, because compliance and integration details tend to surface after the start.

Ready to ship AI for your fintech product?

Tell us about your project. We'll reply within one business day.