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.
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.
After scanning, Trustabl generates fix suggestions for every finding. Safe, low-risk fixes will be applied automatically. Higher-risk changes will be surfaced for your review before anything is committed. Remediation will be available as a VS Code/Cursor extension and as a Skill.md for other agent environments. Coming soon.
Yes. Trustabl is essentially a specialized linter for AI agents. While traditional linters (like ESLint or Ruff) focus on code style, syntax, and general bugs, Trustabl analyzes your AI agents, tools, prompts, and SDK configurations for reliability, safety, and production readiness — flagging patterns that expose you to prompt injection, missing timeouts, tool misconfigurations, and guardrail gaps that standard linters miss. Think of it as "ESLint for AI agents" — it runs in CI/CD, gives clear explanations and fix suggestions, and helps you ship safer, more robust agentic systems.
