SPREAD AI raises $30M Series B for industrial AI

2026-04-29 · Source: Tech.eu - Tech.eu · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Emerging Technologies & Innovation · Depth: Fundamental Awareness, quick

Summary

SPREAD AI has secured $30 million in Series B funding to fuel its international expansion and enhance its industrial AI platform. New investors include DTCP Growth, IQT, OTB Ventures, Salesforce, and Thesiger Capital, with participation from existing backers HV Capital and Nauta Capital. The platform integrates and contextualizes product data across the entire lifecycle, from design to production, enabling manufacturers in sectors like automotive and aerospace to create "Product Twins." This technology helps engineering and operations teams understand dependencies, assess trade-offs, and make faster, more efficient decisions, leading to quicker development cycles, improved troubleshooting, and cost savings. The investment also deepens SPREAD AI's collaboration with Salesforce, aiming to bridge the gap between customer expectations, engineering, and operational execution.

Key takeaway

For Directors of AI/ML in manufacturing seeking to optimize product development and operations, SPREAD AI's platform offers a solution to integrate disparate product data. Your teams can leverage "Product Twins" to gain comprehensive insights, accelerate decision-making, and potentially achieve significant cost reductions and faster development cycles. Consider how an AI-native data foundation could unify your engineering and operational data.

Key insights

Industrial AI platforms integrate product data across lifecycles to enhance manufacturing efficiency and decision-making.

Principles

• Product Twins enable holistic data understanding.
• AI-native data foundations support long-term performance.

Method

Integrate structured and unstructured product data across enterprise systems to create "Product Twins" for improved engineering and operational decision-making.

In practice

• Apply Product Twins for dependency analysis.
• Use AI to streamline troubleshooting processes.

Topics

• Industrial AI
• Series B Funding
• Product Twins
• Salesforce Collaboration
• Manufacturing Efficiency

Best for: Investor, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech.eu - Tech.eu.