Munich-based ClearOps raises €8.6 million Series A to build AI operating system for industrial after-sales - EU-Startups
Summary
Munich-based enterprise SaaS startup ClearOps announced on May 21, 2026, the closing of an €8.6 million Series A funding round. Led by Hitachi Ventures, with participation from Schoeller Group and Barkawi Group, this marks the company's first institutional capital raise. Founded in 2020, ClearOps develops an AI-powered after-sales platform for industrial Original Equipment Manufacturers (OEMs). Its system connects OEMs, dealers, service partners, and machines on a single platform, facilitating parts planning, predictive service operations, and real-time coordination across global networks. ClearOps claims to increase parts availability by up to 40%, drive 5-15% growth in parts sales, and reduce repair times by up to two days for clients like AGCO, Terex, Jungheinrich, and Lippert. The new funding will support global growth, go-to-market expansion, strategic partnerships, and further AI platform development.
Key takeaway
For industrial Original Equipment Manufacturers (OEMs) evaluating after-sales optimization, ClearOps' €8.6 million Series A funding signals growing investor confidence in AI-driven platforms. You should consider integrating AI operating systems to transform fragmented service environments into connected, data-driven ecosystems. This approach can significantly improve machine uptime, boost parts sales by 5-15%, and reduce repair times, directly impacting your profitability and customer loyalty. Explore solutions that offer real-time coordination and predictive capabilities without replacing existing infrastructure.
Key insights
ClearOps secured €8.6 million to scale its AI operating system for industrial after-sales, enhancing uptime and efficiency.
Principles
- Connected service networks improve industrial after-sales.
- Real-time data orchestration drives predictive maintenance.
- After-sales is a significant OEM profit driver.
Method
ClearOps aggregates and orchestrates data across the service supply chain, connecting OEMs, dealers, service partners, and machines on a single platform to predict demand and automate complex parts and service workflows.
In practice
- Implement AI for predictive service operations.
- Integrate OEMs, dealers, and service partners.
- Automate parts planning and service workflows.
Topics
- Industrial After-Sales
- AI Operating System
- Enterprise SaaS
- Series A Funding
- Predictive Service
- OEM Networks
Best for: Investor, Entrepreneur, Executive
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Editorial summary, takeaway, and curation by AIssential. Original article published by Series A" OR "Series B" OR "Series C" AI startup via Google News.