Prove your AI is safe before it becomes an incident.
RedRaven finds the gaps. FireGuard enforces controls continuously in production.
The problem
In fintech, medtech, and insurtech, teams already know the risks: data exposure, policy bypass, unsafe tool actions, and compliance failures.
The hard part is making controls practical, repeatable, and auditable across multiple agents, teams, and releases, while keeping latency low and shipping fast.
Outcomes you can expect
A clear security and compliance gap analysis with pass rates.
Prioritized fixes based on impact and exposure.
Guardrails that enforce the rules in real time with low latency.
Monitoring and evidence for audits and internal risk reviews.
A repeatable process that scales across agents and departments.
Why Fireraven fits regulated AI agents
Fireraven is built for use-case-specific rules, not only generic "safety categories." You can enforce real operational constraints like restricted topics, data handling requirements, and tool/function call boundaries.