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.
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.
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.
Complementary. Trustabl automatically generates OpenTelemetry (OTEL) tracing, structured logging, and metrics configurations that feed directly into LangSmith, Langfuse, or any observability platform. We also surface key aggregated metrics and production readiness insights ourselves.
