They focus on securing the agent runtime and detecting threats. Trustabl focuses on hardening the tools agents use so they are production-safe, policy-compliant, and resilient by design. We prevent problems at the source rather than only detecting them at runtime.
Smarter models can describe tools better, but they cannot reliably harden them for production. Trustabl adds critical production-grade elements models cannot consistently provide: structured validation rules, circuit breakers, policy enforcement, cryptographic attestations, least-privilege OpenShell policies, and SLSA supply-chain provenance.
Trustabl is built for AI engineers, platform teams, and security/compliance teams who are building or running agentic systems in production and want tools that are reliable, observable, and policy-compliant.
No. You have full control. Trustabl auto-applies safe fixes (like adding missing timeouts or standardizing retry logic) and surfaces higher-risk changes for your explicit review and approval. You decide what gets committed.
