Financial institutions operate under the strictest regulatory oversight. Their AI cannot afford hallucinations, data leaks, or ungoverned learning.
Domain-tuned brain for finance.
Live today.
Our finance SLM is fine-tuned on financial services workflows — client communication, compliance documentation, risk assessment coordination, and regulatory reporting. It handles sensitive financial data with full auditability and stays within your institution's guardrails.
Client communication
handling inbound queries about accounts, products, and services with precise, compliant responses in the client's language.
Compliance documentation
generating structured records of every client interaction formatted for your regulatory reporting requirements.
Escalation routing
identifying when a query requires human judgment and transferring it with full context, without the client noticing the handoff.
Encrypted, on-prem deployment for financial networks.
We deploy the financial agent directly into your secure on-premise servers or dedicated cloud network. Client financial records, transaction histories, and proprietary risk models remain strictly within your perimeter. The entire agent architecture runs on an encrypted layer with SOC2 compliance and immutable audit trails.
How It Learns
The agent adapts to market dynamics.
Financial regulations and client needs change rapidly. Your agent learns from real trading queries, wealth management interactions, and compliance workflows without ever leaking proprietary data. Instead of suffering from model drift, the system continuously refines its accuracy, with strict human-in-the-loop governance ensuring total compliance before any update goes live.
Fine-Tuned on Financial Data
Domain-specific SLM trained on your risk models, client histories, and regulatory frameworks.
Adapts From Client Use
The Adaptive Harness refines the agent as it handles complex financial queries in production.
SOC2 Auditable
Every model update is logged and reviewed before going live. Full audit trail at every step.