LTM has launched BlueVerse RightLogic, a cybersecurity assessment and risk assurance framework designed to help enterprises identify, assess and remediate cyber exposure as they accelerate AI adoption.
AI is now capable of autonomously identifying and exploiting vulnerabilities, while exposure across infrastructure, applications and supply chains continue to expand. This has elevated cyber risk from a technology concern to a board-level priority, with enterprises struggling to maintain visibility and respond at the speed of emerging threats.
BlueVerse RightLogic addresses this gap by providing a unified, business-aligned view of enterprise exposure and enabling a shift from fragmented, point-in-time assessments to continuous, evidence-led risk management. The framework combines an end-to-end AI and cyber exposure assessment engine with a structured execution model that spans from assessment to remediation.
At the core of the offering is an innovative, robust cybersecurity assessment model spanning software supply chain risk, legacy systems, network exposure, identity and access controls, AI-specific risks and governance readiness. The framework integrates an outside-in view of adversarial exposure with an inside-out assessment of enterprise readiness across people, process and technology, supported by a dedicated AI-specific risk lens.
“AI-driven threats are autonomous, scalable and continuous, and they demand a fundamentally different approach to cybersecurity. With BlueVerse RightLogic, we enable organizations to quantify exposure, prioritize action and build a defensible security posture that supports safe and scalable AI adoption,” said Krishnan Iyer, Chief Growth Officer, LTM.
Delivered through a structured 4 to 6 week engagement, BlueVerse RightLogic provides rapid diagnostics, deep domain assessments and a board-ready risk summary, followed by a prioritized remediation roadmap. The model extends into execution through a partner-led ecosystem that drives fixes across infrastructure, applications and open-source dependencies, enabling faster response cycles, improved risk visibility and a governed pathway for secure AI adoption at scale.
