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.
Trustabl scans AI agents, tools, and skills for production-readiness issues — flagging reliability, safety, and configuration gaps with clear fix suggestions. Free remediation via VS Code, Cursor, and Skill.md is coming soon. Think of it as a specialized linter for agentic systems.
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.
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.
