We measure trust. We don’t ask you to take it.

Independent by design.

The AI-security market is consolidating: testing tools are being absorbed by the platforms whose agents they test. Molt is independent — we report to you, not to a platform owner. Our findings carry no incentive other than being right.

We test a sealed copy of your agent — never production.

Fisher runs against an approved sandbox, simulated environment, or approved endpoint with synthetic data and canary markers. We may ask for tool shapes, safety rules, and representative tasks. We do not request production access, employee or customer credentials, or real customer records.

Mapped to the standards, frameworks, threat taxonomies, and regulatory regimes your teams use — mapping, not certification.

Depending on scope, relevant findings can be mapped to the OWASP Top 10 for LLM Apps, the OWASP Top 10 for Agentic Apps, the NIST AI Risk Management Framework, MITRE ATLAS, ISO/IEC 42001, GDPR, the EU AI Act, and applicable HIPAA requirements. Mapping is contextual and supports internal analysis. It is not certification, legal advice, or a determination of compliance.

The standard beneath everything we build.

Deep Model Trust is the conviction — and the architecture — that agents must be trustworthy by construction: predictable execution in isolated environments, cryptographically scoped and short-lived credentials, and behavior you can audit and re-derive. Fisher proves where today’s agents break; Deep Model Trust is what we’re building so they don’t.

Explore Deep Model Trust →

An assurance vendor should be easy to assess.

Our public legal and policy documents:

Privacy Policy →  ·  Terms of Use →

We attack safely, and we disclose responsibly.

All testing is authorized, sandboxed, and synthetic. Findings go to you first, with reproduction steps and remediation ownership — never published against you. Our independent model benchmarks measure capability and guardrail behavior on the same rig, with the full run recorded.

View the benchmarks →