Helsinki-based AI platform CloEE has raised €520,000 (US$556,400) in a pre-seed funding round aimed at enhancing its solutions for discrete manufacturing.

The funding round was led by angel investor Miro Vertanen and Innovestor Angel Co-fund, with support from Cariplo Iniziative and three members of the Finnish Business Angels Network (FiBAN).

Founded in 2022 by Oleksandr Zadorozhnyi and Julia Sabitova, CloEE utilizes generative AI to analyze real-time data from manufacturing equipment.

The goal is to optimize overall equipment effectiveness (OEE) and improve operational efficiency.

The company states its platform can be deployed within two weeks, with options for on-premise, offline, or cloud-based implementation.

🔗 Source: EU-Startups

🧠 Food for thought

1️⃣ The booming AI manufacturing market explains investor enthusiasm

CloEE’s €520k pre-seed round comes amid extraordinary growth projections for AI in manufacturing, with market forecasts showing exceptional expansion rates.

The global AI manufacturing market is projected to grow from USD 3.45 billion in 2023 to USD 47.02 billion by 2032, representing a compound annual growth rate of 33.68%1.

Some analysts project even more dramatic growth, with forecasts reaching as high as USD 695.16 billion by 2032, reflecting the transformative potential investors see in manufacturing AI2.

This funding environment explains why CloEE secured investment from multiple sources despite being at an early stage, as investors recognize the opportunity in solving manufacturing efficiency challenges through AI.

The backing from both angel investors and funds like Innovestor Angel Co-fund demonstrates confidence in the specific niche CloEE targets, connecting manufacturing equipment and applying AI analytics to improve operational efficiency.

2️⃣ Addressing the $50 billion downtime problem drives adoption

CloEE’s focus on equipment efficiency addresses a massive, documented pain point in manufacturing, with unplanned downtime costing manufacturers over USD 50 billion annually1.

The company’s claim that “70% of manufacturers struggle to reach even 50% equipment efficiency” aligns with industry research showing that predictive maintenance and real-time monitoring can significantly reduce these costs.