Verusen, the industry leader driving AI for MRO (maintenance, repair, and operations) supply chain and inventory optimization, launched its groundbreaking Explainability AI Agent for data and context-driven material and inventory optimization. This first-of-its-kind capability delivers unprecedented transparency into Verusen’s stocking policy recommendations, enabling procurement, operations, and supply chain teams to trust, understand, and confidently act on AI-driven insights, accelerating smarter execution and enterprise-wide alignment.
Verusen is Transforming MRO with Purpose-Built AI Agents
Verusen’s Material Graph – the world’s largest MRO materials knowledge base – has ingested over 41 million unique SKUs, $12 billion in annual inventory and spend, and all associated transactional POs. This powerful platform redefines how asset-intensive enterprises manage critical materials inventory, procurement, and risk across their global MRO supply chains.
By integrating Large Language Models (LLMs), Machine Learning, and Natural Language Processing technologies, Verusen transforms manual, disconnected inventory management practices into streamlined, context-rich optimization strategies-empowering teams to make smarter decisions faster while reducing risk and operational costs.
Also Read: Softeon and Extolla Announce Strategic Partnership to Deliver Global Supply Chain Innovation
Explainability AI Agent: Turning the Black Box into a Trusted Engine
Humans need to be able to understand and trust AI reasoning processes and have insights into the decisioning. According to global management consultant firm McKinsey & Company, by shedding some light on the complexity of so-called black-box AI algorithms, explainability can increase trust and engagement among those who use AI tools. This is an essential step as AI initiatives make the difficult journey from early use case deployments to scaled, enterprise-wide adoption.
Enterprises adopting AI for MRO management often struggle with the “black box” problem-trusting recommendations without understanding the logic behind them. Verusen’s Explainability AI Agent eliminates this barrier by providing clear, concise insights into every recommendation’s rationale, supported by a powerful feedback loop that continuously learns and adapts based on user interactions.
SOURCE: GlobeNewswire