LatticeFlow AI Platform Connects Governance Frameworks with Continuous AI Risk Monitoring
LatticeFlow AI launches a platform to bridge the gap between AI governance frameworks and technical controls, enabling continuous risk monitoring for autonomous systems.
LatticeFlow AI has introduced a new platform designed to tackle the growing challenge of managing risks associated with autonomous AI systems. As organizations increasingly deploy AI in critical business processes, traditional governance methods, often reliant on documentation and periodic assessments, are proving insufficient to keep pace with the dynamic nature of AI risks.
The LatticeFlow AI Platform aims to bridge this gap by directly linking AI governance frameworks with technical controls. This integration allows for the continuous generation of evidence and the translation of evaluation results into actionable risk insights. The platform provides organizations with the means to assess their AI systems and make informed governance decisions throughout the AI lifecycle.
At its core, the platform unifies AI discovery, evaluation, and governance into a single system. This comprehensive approach enables organizations to maintain an inventory of their AI assets, rigorously evaluate their performance and security, and govern them effectively. It supports a range of AI implementations, from foundational models and enterprise applications to sophisticated autonomous agents, ensuring continuous monitoring as models, data, and threat landscapes evolve.
Specifically designed for agentic AI, the LatticeFlow AI Platform facilitates use-case-specific evaluations, adaptive red teaming, and ongoing monitoring. This adaptive capability re-evaluates systems as they change, proactively identifying and managing emerging risks. "AI governance has long lacked a technical foundation," stated Dr. Petar Tsankov, CEO of LatticeFlow AI. "There has been a persistent gap between what governance frameworks require and what organizations can actually measure. By connecting frameworks directly to technical controls, we enable enterprises to understand, control and govern AI risk with evidence, continuously."
A key component of the platform is AI Atlas, a public registry that maps over 40 AI governance frameworks—including the EU AI Act, OWASP, NIST, ISO 42001, and FINMA—to technical risk controls and ready-to-run evaluations. AI Atlas translates governance requirements into measurable controls, allowing organizations to run evaluations through the LatticeFlow AI Platform. This process generates verifiable evidence, provides risk interpretations, and offers board-level visibility into AI risk.
This approach signifies a broader industry shift in AI governance, moving from static compliance documentation to the continuous generation of technical evidence against recognized global frameworks. Dr. Apostol Vassilev, Leading Expert in Trustworthy and Responsible AI and Cybersecurity at NIST, commented, "AI governance can no longer be treated as a static verification problem. Because we cannot build a flawless, permanent wall around AI systems, security and governance must evolve beyond cyclical, paper-driven reviews and move directly into the operational runtime to continuously measure, constrain, and manage risk throughout the operational lifecycle."
The platform has already seen adoption in enterprise settings, including with organizations like SAP and Axpo, as well as AI innovators such as Unique AI. LatticeFlow AI's approach has also been recognized in the 2026 Gartner Magic Quadrant for AI Governance Platforms, where it was noted as a pioneering vendor shifting the market towards evidence-based AI governance. "Innovation only scales when it's built on trust," said Dr. Sina Wulfmeyer, Chief Data Officer at Unique AI. "As AI moves into core investment and advisory workflows, we need continuous technical evidence that our systems are reliable, transparent and safe."
As agentic AI becomes more prevalent in enterprises, the limitations of policies and documentation alone are becoming apparent. The LatticeFlow AI Platform addresses this by providing the continuous technical evidence necessary for organizations to effectively understand and control AI risk, ensuring that AI adoption can scale responsibly and securely.