Arthur AI is an AI delivery and governance platform for enterprise-grade MLOps, with the goal of unifying the teams responsible for security, finance, and delivering AI onto a single control plane, enabling trusted, measurable, monitorable, and governable enterprise-grade AI operations at scale.
Main capabilities
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Agent discovery and governance Arthur's discovery capability can find every agent running anywhere on endpoints, in the cloud, in private data centers, and in compute environments, including shadow agents. The platform provides a centralized view to coordinate every AI initiative across the enterprise, enabling AI leaders, builders, and security teams to uniformly enforce policies and ensure AI remains under control.
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Observability The platform can show every agent running in the enterprise and provide insight into its internal workings. Full observability can trace every step of reasoning, tool calls, retrieval, and handoff, making it possible not only to see what an agent did, but also to understand why it did it, including: visibility into all agents in a single inventory (including shadow agents), step-level tracing of reasoning/tools/retrieval, and uniform enforcement of global and use-case-level policies everywhere. The official page also gives example prompts such as "The retrieval window is too small for claims queries, expected relevance improvement 0.11, apply?" as well as governance and security event examples such as "Prompt injection blocked (claims-copilot)," "Abnormal tool sequence (procurement-agent)," and "Data exfiltration spike (support-agent-v4)."
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Runtime security Guardrails and security policies can be deployed quickly to provide real-time protection. Arthur's Agent Behavioral Analytics (ABA) continuously monitors every AI application running in the company and immediately alerts on anomalous behavior, suspicious patterns, and indicators of compromise, and can stream findings into the tools the security operations center (SOC) already uses.
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Cost control The platform can track AI spending by team and by user; automatically detect requests that do not need expensive models and reroute them, including routing to internally hosted open-source models. Monitor and control AI usage through a single view while ensuring service quality.
How to use
According to the materials, Arthur's runtime security can "go live in minutes and monitor around the clock." The platform provides detection and runtime security, governance/audit/compliance capabilities for CISOs and security teams (complete audit logs and lineage, as well as continuous risk assessment behind every policy decision, and can prove controls on demand); for CAIOs, product builders, and engineering leaders, it provides capabilities covering the entire agent development lifecycle, from prompt experimentation to continuous evaluation, helping deliver trustworthy and reliable AI.
Applicable scenarios
It is suitable for organizations that need security, governance, audit, compliance, and cost management for enterprise AI and agents, especially enterprise environments where security, audit, and governance teams need to share the same "source of truth." The materials mention that it is trusted by Fortune 500 leaders and cover topics such as AI agent governance in federal environments (a FISMA-aligned approach) and a builder's guide to operating AI agents under the EU AI Act.
Limitations
The materials do not provide details such as specific deployment methods, supported models or platform lists, pricing and charging models, or specific integration lists; this content is not available at this time.
