Financial Services & FinTech
Agents that decide, execute, and learn — not just flag and wait.
Most fintech AI watches transactions and waits for humans to act. By the time your team reviews the alert, the fraud has cleared. The customer has churned. The backlog has grown.
We build agentic AI that makes decisions autonomously — detecting fraud rings in real-time, processing documents with reasoning, and letting customers transact through conversation. Your team oversees and improves; the agents execute.
Your infrastructure. Your data. Yours to own.
Why Agentic
Transaction-level fraud scoring
Graph-based fraud ring detection
Rules-based credit decisions
RL-optimised, continuously learning policies
Field extraction from documents
Reasoning and context understanding
Alert and wait for human
Decide within guardrails, escalate exceptions
Chatbots that answer FAQs
Conversational agents that transact
Batch personalisation
Real-time, context-aware personalisation
Brittle workflows that break
Self-healing workflows that adapt
What We Build
Agentic AI systems for financial services
Graph-Based Fraud Detection
GNNs that detect fraud rings, coordinated attacks, and network-level anomalies — not just individual transaction flags
Autonomous Decisioning
Agents that make credit, fraud, and onboarding decisions within defined guardrails — humans supervise, not execute
Reasoning Document Processing
LLMs that understand documents — context, intent, inconsistencies — not just extract fields
Conversational Banking Agents
Customers query balances, initiate transfers, dispute charges, and resolve issues through natural language
Self-Healing Workflows
Agents that detect process failures, route around exceptions, and escalate only what truly needs human judgment
Reinforcement Learning for Credit
Policies that learn from outcomes — adapting limits, pricing, and risk thresholds continuously
Real-Time Personalisation
Agents that tailor offers, rates, and experiences in the moment — not batch segments
Network Intelligence
Transaction-level monitoring misses coordinated attacks. We build graph neural networks that see relationships, patterns, and risk propagation across your entire entity network.
Fraud ring detection
Identify coordinated activity across accounts, devices, and behaviors
Relationship mapping
Hidden connections surfaced automatically
Coordinated attack detection
Patterns invisible to rules-based systems
Risk propagation
See how risk spreads across your network
Continuous learning
Models improve from analyst feedback via RLHF
Agentic AI in Action
Real AI agents working together autonomously to deliver results in your industry. Select a scenario and watch them work.
This is the exact agent architecture we deploy for clients today.
Synthetic data for privacy. Architecture identical to live client deployments.
From the Field
Fewer false positives
European digital bank, 10 weeks from kickoff to production.
Graph-based fraud detection + adaptive learning reduced analyst workload while improving catch rate.
Most of our work is deep IP creation. Our clients protect what they're building. So do we.
But we can walk you through how we built it and what it achieved.
Talk to an EngineerTechnical Foundations
How we build agentic AI for finance & fintech, deployed on your infrastructure: cloud, on-prem, or hybrid. Swiss/EU data residency supported.
Deployed on your infrastructure — cloud, on-prem, or hybrid. Swiss/EU data residency supported.
From kickoff to production system. Not a demo—a working system on your infrastructure.