List your company

Agent Development Toolkit

AI evaluation and observability · by Arthur

Open-source toolkit for building, testing, and monitoring AI agents in production.

Visit website

What it does

Open-source toolkit for building, testing, and monitoring AI agents in production. Provides prompt versioning, structured A/B experiments, end-to-end tracing, and live evaluations. Part of the Arthur Engine.

  • AI governance and policy enforcement
  • AI performance monitoring
  • LLM evaluation
  • agent observability and tracing
  • agent discovery and inventory
Category
AI evaluation and observability
Users
enterprise security teams, audit teams, governance teams, engineering teams and 1 more
Public API
Not offered
Deployment
Self-hosted

Not yet disclosed: platforms, languages and support channels.

Pricing

  • Free plan$0

Prices as published by Arthur, checked Oct 2026.

Security and compliance

As reported by Arthur. Ask for audit reports before you buy.

  • SOC 2Compliant
  • HIPAACompliant
  • ISO 22301Compliant
  • NIST CSFCompliant
  • FedRAMPCompliant
  • RBAC (Role-Based Access Control)
  • SSO (Single Sign-On)
  • Immutable audit logs

Reviews

No reviews yet

Reviews come from people who use Agent Development Toolkit at work. Share how your team uses it to help other buyers decide.

Write a review

Alternatives

  • Tokenshire

    by Olam Labs

    Simulated town of AI agents running autonomously for long horizons, socializing and managing government, economy, and resources under constraints.

  • DataCenterBench

    by Robocurve

    Evaluating robots on data-center construction tasks, including racking servers, routing cable, and the physical work behind the compute supply chain.

  • LLM evaluation

    by Openlayer

    Rigorous evaluation for GenAI and LLMs—test every prompt, trace every response, and validate every output.

  • Self Diagnostics

    by Raindrop

    Capability for agents to proactively report their own failures via SDK instrumentation.

  • MangoDesk

    Evaluates and improves AI on meaningful use cases via production-grade RL environments, accelerating custom evals and post-training data creation.

  • Loss Analyses

    by AfterQuery

    Identifies where and why models fail in professional contexts through systematic study, pinpointing the precise failure modes and distributional gaps that inform dataset and env...

Is this your product?

Claim it to keep details accurate and submit evidence for the next ranking review.

Claim Agent Development Toolkit