Fisher is available now for independent adversarial testing and production-readiness evidence. Additional Deep Model Trust capabilities run in production.
Fisher pressure-tests real, tool-using AI workflows across permissions, data boundaries, and multi-turn attack paths. It verifies outcomes in tool calls and state changes, replays confirmed findings, and returns reproducible evidence for security, governance, and release decisions.
Start with a fixed-scope 30-Day Agent Assurance Assessment, then extend the same attack → prove → remediate → re-test loop across future releases.
Deep Model Trust is Molt’s technical architecture for moving from testing agent behavior to building systems whose authority, decisions, and release processes are bounded and verifiable. Fisher is the first commercially available product built around that thesis. Testing is where trust starts, not where it ends.
Fisher’s adversarial evidence informs how we’re building a trustworthy agent architecture — small, domain-trained models, scoped authority, and provable behavior. Each component below carries its published status.
One priority workflow, fixed scope, reproducible evidence your security and governance teams can act on.
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