Dispatch, records, and investigative AI systems don't get a second chance at a failure. RedLens tests for containment escapes and adversarial attacks before deployment, runs fully air-gapped when your environment requires it, and maps every finding to the NIST AI RMF.
Download Solution Sheet (PDF)For environments that can't route traffic to an external service, a full self-hosted Docker deployment is available on the Enterprise tier, using an on-premise model with no outbound dependency required to run assessments.
A dispatch or records AI that breaks containment can take unauthorized actions or expose data outside its intended scope. RedLens tests specifically for this: network escape, behavioral deviation, and micro-step attack chains an agent could use to step outside its boundary.
RedLens generates synthetic, clearly-labeled dispatch and records-style data for testing: mock incident logs, unit IDs, and case identifiers, none derived from real calls or records. Your dispatch-assistance or records-query AI gets tested under realistic adversarial conditions without any real, sensitive data entering the assessment.
Every RedLens finding maps to the NIST AI Risk Management Framework, and Enterprise deployments can add a custom SLA negotiated as part of the engagement. We're direct about what that does and doesn't mean for agencies with formal certification requirements.
Mission-critical public safety systems are exactly the kind of high-consequence environment general-purpose AI security tools weren't built to test.