Financial Services
Model risk management and operational resilience for AI.
Supervisory frameworks such as SR 11-7 and DORA expect firms to know which model ran, show that agents stayed within policy, and keep a credible exit plan from any single provider.
What VAIL verifies
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Governance and compliance
Keep a timestamped record of which model ran, when, and where it came from.
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Continuous behavioral monitoring
Probe live agents on a schedule to confirm they behave as intended and stay within policy.
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Model independence
Know your agents will hold up on a new model or provider before you switch.
Built for
- Stakeholders
- Chief Risk Officers, model risk management teams, compliance and audit, and AI architecture leads.
- Deployment
- No SDK, no trace access, and no customer data read. Managed, in your cloud, or air-gapped.
Research
All publications-
ACM CAIS 2026 · Demo
Behavioral Fingerprints for LLM Endpoint Stability and Identity
Detects changes to a vendor model's family, version, inference stack, and quantization behind an unchanged API name.
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VAIL Substack
Misbehaving Agents and the Impacts of Extreme Instability
Endpoints with extreme behavioral instability show matching instability in agent tool calls.
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Cisco and VAIL · 2026
Models don't have passports: AI lineage crosses organizational and geographic borders
Establishes where a third-party model came from before it is approved.
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VAIL White Paper · 2025
Security Assurances for AI in High-Stakes Environments using Verifiable Computation
Why high-consequence financial decisions need cryptographic evidence of which model produced them.
Go further
Request an assessment.
Tell us which model or agent you need verified. We reply within one business day with a scope and a start date.
Or write to contact@projectvail.com