Arthur
by Arthur
One control plane to discover, monitor, and govern AI agents and models in production
Arthur is an enterprise AI observability, security, and governance platform that helps teams ship reliable AI agents and models, with continuous monitoring, guardrails, and a first-of-its-kind Agent Discovery & Governance (ADG) layer. It is built for security, risk, and AI teams that need to see, evaluate, and control agentic AI in production.
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing
- Target Market
- CISOs, CIOs, AI/ML Governance Leaders, Data Scientists
- Founded
- 2018
- Headquarters
- New York, New York, United States
Key Features
- ✓Agent Discovery & Governance (ADG)
Detects agents across the enterprise via OpenTelemetry, MCP monitoring, network traffic, and platform APIs, surfacing shadow agents deployed without central IT awareness.
- ✓Runtime guardrails
Pre-LLM checks screen for sensitive data and injection attacks while post-LLM validation catches hallucinations and harmful outputs, with self-correcting loops.
- ✓Continuous evaluation
Unsupervised binary evaluations run on production traffic to measure hallucination risk, response completeness, goal accuracy, and topic consistency.
- ✓Observability on open standards
Built on OpenInference/OpenTelemetry conventions for end-to-end visibility across LLM calls, RAG retrievals, and tool invocations.
- ✓Federated, in-VPC deployment
A federated architecture keeps sensitive inference data inside the customer's VPC, with SaaS, on-prem, and GCP/AWS marketplace options.
Capabilities
Use Cases
- •Shadow-agent discovery
Find and inventory autonomous agents running across multi-cloud environments before they create compliance or security risk.
- •LLM output safety
Block prompt-injection, PII leakage, and hallucinated or harmful responses in real time before users see them.
- •AI audit and compliance
Generate evaluation and audit evidence mapped to the EU AI Act, NIST AI RMF, and ISO 42001.
Ideal For
Best For
- ✓Discovering and governing AI agents (including shadow agents) in production
- ✓Guardrailing LLM apps against prompt injection, data leakage, and hallucinations
- ✓Meeting AI governance mandates aligned to the EU AI Act, NIST AI RMF, and ISO 42001
Integrations
Deployment
Market Analysis
Pros
- ✓Agent-native governance built for the agentic era
- ✓Strong regulatory mapping (EU AI Act, NIST AI RMF, ISO 42001)
- ✓In-VPC federated deployment protects sensitive data
Cons
- ✗Crowded AI-governance/observability market
- ✗Enterprise pricing not transparent
Pricing
Enterprise
Contact for pricing
- ✓Agent Discovery & Governance
- ✓Runtime guardrails
- ✓Continuous evaluation and observability
- ✓Federated in-VPC deployment
Enterprise pricing is not publicly disclosed; Arthur also maintains open-source components and is available on the Google Cloud and AWS marketplaces.
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