Magentic closed an $18 million Series A led by Felicis (with Sequoia and The Westly Group) to scale its multi agent AI digital workers for end to end procurement and supply chain automation at major manufacturers.
Magentic’s $18 million Series A funding represents a significant acceleration for the New York and London based startup building AI “digital workers” (called Mages) for procurement and supply chain operations at large manufacturers. The round was led by Felicis, with participation from existing investors Sequoia Capital and The Westly Group. It follows a $5.5 million seed round in July 2025 (led by Sequoia, with The Westly Group, First Momentum Ventures, and angels from SAP, Airbus, McKinsey, Hugging Face, and others), bringing total funding to $23.5 million in roughly 14 months since launch.
The capital will accelerate the AI agent roadmap, expand coverage across more procurement and supply chain workflows (both direct and indirect spend), and deepen long horizon AI research focused on complex optimization problems involving large scale, multimodal data.
What is Magentic?
Magentic was founded by Robin Van Aeken (CEO, former McKinsey supply chain consultant) and Odhran O’Donoghue (CTO, machine learning PhD with experience at OpenAI, NASA, and the Crick Institute). The pair first connected through Oxford hackathons. The company launched in July 2025 and targets the operational realities of Global 500 manufacturers: billions of data rows, tens of billions in spend, legacy ERPs, Excel heavy processes, and fragmented systems.
Its multi agent systems act as virtual employees that work inside existing tools, Microsoft Teams, email, and internal systems, rather than requiring new dashboards. They handle end to end workflows: “make versus buy” decisions, supplier selection, contract negotiation, order placement, invoice clearing, category strategy, spend analysis, should cost modeling, compliance enforcement, and value recovery (price leakage, rebates, off-contract charges). Human oversight remains for critical approvals. The platform supports both indirect spend and the more complex direct spend on raw materials.
Security features address enterprise concerns about autonomous agents in critical systems, including zero data retention agreements with major AI providers, flexible cloud deployment, and isolated regional deployments. Certifications and alignments include ISO 27001, GDPR, SOC 2, and the EU AI Act.
Early results include one Global 500 customer processing more than one million orders annually via the agents and another realizing $4 million in savings. Across the customer base (including Global 500 firms and three of the world’s ten largest beverage producers), typical outcomes are 2–5% spend savings, a 60% improvement in data quality, and the elimination of tens of thousands of hours of manual work. Case studies highlight 4% savings on MRO spend at a $40 billion manufacturer and the uncovering of 25% supplier document errors. The company positions the technology as increasing the value of human procurement teams rather than replacing them.
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The raise occurs amid rising pressure on industrial and procurement teams from manufacturing demand growth, tariffs, geopolitical disruption, and constrained budgets. Procurement workloads have grown roughly 10% year over year against only about 1% budget growth. Goldman Sachs projects approximately $8 trillion in AI related capital spending from 2026–2031, much of it requiring physical infrastructure that must be sourced and built. McKinsey data cited by the company indicates supplier compliance issues can waste about 2% of spend (roughly $40 million on a $2 billion budget).
Magentic differentiates by aiming for full process ownership across direct and indirect spend for the largest industrial buyers, in contrast to more narrowly focused competitors in negotiation automation or specific agent use cases. Investors highlight the difficulty of embedding agents deeply enough in complex, legacy manufacturer systems as a key barrier that few others have cleared for the “physical economy.”
Felicis partner Feyza Haskaraman emphasized the consequential yet under automated nature of supply chains and the technical challenge of enabling agents to act reliably inside manufacturers’ environments. CEO Van Aeken frames the opportunity around compounding competitive advantage through better intelligence amid the largest historical capex cycle driven by AI demand. CTO O’Donoghue stresses the need for systems that diagnose, plan, act, and complete work across terabytes of multimodal data beyond typical context window limits.
The funding positions Magentic to scale its AI workforce offering deeper into industrial operations at a moment when physical world procurement and supply chain complexity is intensifying.
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