How much does Arthur cost?

Arthur uses a freemium model. The Free tier is $0/month, Premium is $60/month, and Enterprise pricing is custom. You can also self-host via Docker, CloudFormation, or Helm, or start on the hosted SaaS free tier.

Which AI frameworks does Arthur integrate with?

Arthur is model- and framework-agnostic. It slots into OpenAI, Anthropic, LangChain, LlamaIndex, and the Vercel AI SDK without forcing a proprietary runtime. It is designed for teams who need observability without rebuilding their existing stack.

Arthur

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

Freemium· Free: $0/mo · Premium: $60/mo · Enterprise: CustomEvaluationMulti-model7.1 / 10

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In short

Arthur is an open-source, OpenTelemetry-native toolkit for tracing, evaluating, and managing production AI agents. It supports prompt versioning, A/B testing, and security checks across multiple LLM frameworks.

Best for

Pick Arthur if you're shipping agents to production and want an open-source, OpenTelemetry-native control plane for prompts, traces, and evals.

Skip if

Skip it if you're a solo builder prototyping a chatbot — the lifecycle tooling is overkill before you have real traffic to evaluate against.

Arthur's Agent Development Toolkit is an MIT-licensed framework for managing the full lifecycle of LLM-based agents in production. It bundles prompt versioning with rollback, A/B experimentation against real traffic, OpenTelemetry-based tracing of every agent step, and continuous evaluations that flag hallucinations, PII leaks, and prompt-injection attempts.

It's aimed at engineering teams who have moved past prototyping and need observability and governance without rebuilding their stack. The toolkit is model- and framework-agnostic — it slots into OpenAI, Anthropic, LangChain, LlamaIndex, and the Vercel AI SDK rather than forcing a proprietary runtime. You can self-host via Docker, CloudFormation, or Helm, or start on the hosted SaaS free tier; enterprise SaaS plans are available on request.

Arthur the company has a longer history in classical ML monitoring (model bias, drift, performance), and this agent toolkit is its bet on the LLM-eval era. The open-source repo, Helm-chart deployability, and OpenTelemetry standardisation make it a credible alternative to closed eval platforms like Braintrust or LangSmith.

Editor's take

Arthur's pivot from classical ML monitoring into agent observability lands well: an MIT licence, OpenTelemetry plumbing, and Helm charts make it one of the few credible self-hostable answers to Braintrust and LangSmith. The agent toolkit is young, but the bones — and the company behind them — are serious.

— The AI Tool Bible editorial team

Pros

✅ MIT-licensed and self-hostable via Docker, Helm, or CloudFormation
✅ Built on OpenTelemetry so traces flow into existing observability stacks
✅ Framework-agnostic: works with LangChain, LlamaIndex, OpenAI, Anthropic, Vercel AI SDK
✅ Covers full lifecycle: prompt versioning, A/B testing, tracing, and online evals
✅ Includes guardrail evaluators for PII and prompt injection out of the box

Cons

⚠️ Agent toolkit is newer than the company's ML-monitoring heritage; ecosystem still maturing
⚠️ Self-hosting Helm/CloudFormation deployment expects real DevOps capacity
⚠️ Paid SaaS pricing is gated behind sales contact

Use cases

agent-evaluationprompt-managementllm-tracinghallucination-detectionprompt-injection-defense

Frequently asked

How much does Arthur cost?: Arthur uses a freemium model. The Free tier is $0/month, Premium is $60/month, and Enterprise pricing is custom. You can also self-host via Docker, CloudFormation, or Helm, or start on the hosted SaaS free tier.
Which AI frameworks does Arthur integrate with?: Arthur is model- and framework-agnostic. It slots into OpenAI, Anthropic, LangChain, LlamaIndex, and the Vercel AI SDK without forcing a proprietary runtime. It is designed for teams who need observability without rebuilding their existing stack.
Is Arthur suitable for solo developers?: It is not recommended for solo builders prototyping a chatbot. The lifecycle tooling is considered overkill before you have real traffic to evaluate against. It is best for engineering teams that have moved past prototyping and need production observability.
What specific issues can Arthur detect?: Arthur’s continuous evaluations flag hallucinations, PII leaks, and prompt-injection attempts. It also provides OpenTelemetry-based tracing of every agent step, prompt versioning with rollback, and A/B experimentation against real traffic to ensure governance and quality.
How does Arthur compare to closed platforms?: Arthur is an MIT-licensed, open-source alternative to closed eval platforms like Braintrust or LangSmith. Its open-source repo, Helm-chart deployability, and OpenTelemetry standardisation make it a credible option for teams preferring open standards and self-hosting capabilities.