TLDR: SplxAI Inc. has launched AI Asset Management, an extension of its platform designed to provide enterprises with unparalleled visibility and security for their AI models, agentic workflows, and underlying infrastructure. This solution integrates AI Bill of Materials generation, vulnerability scanning, and agentic workflow analysis to help security and engineering teams map, inventory, and protect every component of their AI stack, addressing a critical gap in AI adoption.
SplxAI Inc., a leading security platform specializing in artificial intelligence, announced today the release of its new AI Asset Management solution. This strategic extension to the existing SPLX platform aims to equip enterprises with deep visibility into their entire AI ecosystem, encompassing AI models, complex agentic workflows, and the supporting infrastructure. The launch addresses the growing need for robust security measures as AI adoption accelerates across industries.
AI Asset Management is a comprehensive offering that combines several critical security functionalities into a single, unified solution. Key features include AI Bill of Materials (AI-BOM) generation, which provides a detailed inventory of all AI components; advanced vulnerability scanning to identify potential weaknesses; and sophisticated agentic workflow analysis. This integrated approach empowers security and engineering teams to meticulously map and secure every element within their enterprise AI stack.
Kristian Kamber, co-founder and Chief Executive of SplxAI, highlighted the urgency of this development: “AI adoption is accelerating, but most enterprises don’t even know what models and workflows are active across their stack. With AI Asset Management, SPLX closes that gap, giving security leaders not only visibility but also clarity on how workflows behave, how agents interact and where the risks lie, so they can act before attackers do.”
The solution builds upon SPLX’s existing Agentic Radar, an open-source tool for scanning and mapping agentic workflows, transforming its capabilities into an enterprise-grade product. Enhancements include advanced model benchmarking, more granular vulnerability detection, and compliance mapping, ensuring that AI systems adhere to regulatory frameworks and internal policies at scale.
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Through its agentic workflow discovery and visualization capabilities, AI Asset Management meticulously maps every node, agent, and tool within complex AI workflows. This allows organizations to gain a clear understanding of system interactions, identify interdependencies, and uncover potentially risky connections. Furthermore, the platform incorporates agent-level threat analysis, which detects vulnerabilities in individual agents and tools, benchmarking them against established risk scores to provide real-time, prioritized security insights. The system also integrates AI Bill of Materials with security benchmarks, linking discovered models to SPLX’s extensive database to generate comprehensive security, safety, and business alignment scores. Additional features include automated discovery and vulnerability scanning for Model Context Protocol (MCP) servers, ensuring a holistic security posture across the AI landscape.
