- Helsinki-based CloEE (founded 2022) raised about $600K (€520K) pre-seed to expand its AI platform for discrete manufacturing.
- The round, backed by European angels and co-investment funds, will fund scaling deployments, sales in the Nordics/Italy/U.S., and R&D on AI agents.
- CloEE says it is connected to ~25,000 machines in 25 countries and can deploy in about two weeks on-premise, offline, or in the cloud.
- Early U.S. traction includes a pilot with a 100-facility operator and talks for a three-year, 10-site contract, while impact claims (energy, downtime, revenue) still need broader validation.
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CloEE’s pre-seed raise enters at a pivotal moment in industrial AI, a domain under pressure to show real operational and financial impact. The size of the raise—$600K—is typical for early stage European industrial AI startups, especially when backed by angel networks plus co-investment funds, suggesting a broadly optimistic but risk-aware investor sentiment.
By targeting discrete manufacturing sectors with plug-and-play AI that integrates with existing equipment, MES, and ERP systems, CloEE is positioning itself to solve the frequently cited “data gap” issue in industrial operations—specifically, that many factories lack usable data streams or the tools to extract value from them. The claim that 70% of manufacturers can’t reach even 50% equipment efficiency substantiates a large addressable market.
The geographic focus—Nordics, Italy, and particularly the U.S.—raises both opportunity and challenge. The U.S. market offers scale and willingness to invest in digital transformation; however, success will depend on navigating regulatory, compliance, and deployment complexity in environments with legacy systems. CloEE’s current pilot with a U.S. customer operating 100 facilities demonstrates early movement, though actual contracts (e.g., the three-year one under negotiation) will be critical in proving commercial viability.
Performance metrics claimed—energy savings, emergency outage reduction, measurable revenue uplift—are impressive but should be viewed with caution until validated independently or disclosed in more detail. Open questions include how replicable these results are across different industries or machine types, what level of customization is required per client, and how much sales cycle friction exists for non-traditional heavy-manufacturing customers.
From an investment banking viewpoint, the valuation implied by a $600K pre-seed raise and the goal of 20 recurring customers in 2025 suggests a runway of 12–18 months if growth and expenditure are well-managed. The upcoming round will need to show scalable revenue models and unit economics. Partnerships, reference customers (Hyundai mentioned), and pilot-to-contract conversions will be key value inflection points.
Supporting Notes
- CloEE raised approximately $600,000 (≈ €520K) in pre-seed funding on June 23, 2025, led by Miro Vertanen and the Innovestor Angel Co-fund, with participation from Cariplo Iniziative and three Finnish Business Angels Network members.
- The funding will be used to scale existing customer deployments, expand into the Nordics, Italy, and U.S., and develop AI Agents with potential to replace traditional heavy manufacturing platforms.
- CloEE has connected its platform to about 25,000 machines in 25 countries and is piloting with a U.S. customer operating 100 facilities; there are discussions underway for a three-year contract covering 10 of those facilities.
- Performance claims include up to $1 million in annual revenue growth for customers, a 30% reduction in energy consumption, and a 95% reduction in emergency outages; deployment can occur on-premise, offline, or in cloud in two weeks.
- The startup is founded in 2022 by Oleksandr Zadorozhnyi (CEO) and Julia Sabitova (COO), has eight employees, and would like to secure 20 recurring customers by end of 2025 before raising its next financing round.
- CloEE targets manufacturers struggling with production downtime, low overall equipment effectiveness, high defect rates, and rising energy usage; it emphasises cost-free initial implementation to lower barriers to adoption.