Keeping critical assets running has always been a challenge for industries that depend on heavy equipment and complex operations. Many companies still rely on manual data entry, outdated spreadsheets, and reactive maintenance. Fracttal was created to tackle this problem head-on.
The Madrid-based company offers an AI-powered maintenance management platform that helps organisations predict failures before they occur, streamline maintenance scheduling, and centralise all aspects of asset management in one place.
Today, the company closed a $35 million growth round led by Riverwood Capital, with continued backing from Seaya Ventures, Kayyak, GoHub, and Amador.
Turning maintenance from a burden into a source of insight
Fracttal’s story goes back to CEO and co-founder Christian Struve, who saw firsthand how outdated maintenance systems held companies back. He noticed that teams were constantly reacting to problems instead of preventing them, often working with disconnected data and inefficient processes.
Fracttal’s core platform, Fracttal One, pairs AI with cloud-based management tools to forecast maintenance needs, extend asset lifecycles, and minimise downtime. The system integrates with enterprise software and IoT sensors to capture and interpret real-time data from machinery and equipment.
Its line of IoT devices, Fracttal Sense, complements the software by monitoring environmental conditions such as temperature and vibration, feeding data back into the predictive models that power the platform.
Unlike traditional maintenance systems such as Fiix, IBM Maximo, or UpKeep, which focus primarily on digitising checklists and work orders, Fracttal’s approach centres on prediction and automation. The company refers to this as “Maintenance Intelligence.”
What’s next?
The new funding will speed up product development, strengthen Fracttal’s AI capabilities, and support expansion across Latin America and Europe.
TFN contacted Fracttal for comment regarding diversity and inclusion; no response was received at the time of publication.
