SPREAD AI Closes $30 Million Series B for Industrial Engineering Data Platform

--- headline: "SPREAD AI Closes $30 Million Series B for Industrial Engineering Data Platform" slug: spread-ai-30m-industrial-engineering category: llms-genai story_number: "08" date: 2026-04-30 author: The Vault AI sources: - name: Tech.eu url: https://tech.eu/2026/04/29/spread-ai-raises-30m-series-b-for-industrial-ai/ domain: tech.eu - name: BeBeez International url: https://bebeez.eu/2026/04/29/as-europe-pushes-for-ai-sovereignty-germanys-spread-raises-e25-million-to-scale-industrial-ai/ domain: bebeez.eu - name: The SaaS News url: https://www.thesaasnews.com/news/spread-ai-raises-30m-in-series-b domain: thesaasnews.com - name: TechStartups url: https://techstartups.com/2026/04/30/top-startup-and-tech-funding-news-april-30-2025/ domain: techstartups.com ---

Berlin-based startup bets that the real AI bottleneck in manufacturing is not models -- it is the decades of fragmented engineering data that no model can reach.

---

The factories of the future will run on AI, but first someone has to untangle the data. SPREAD AI, a Berlin-based startup building what it calls an Engineering Intelligence platform, has raised $30 million in Series B funding to do exactly that -- connecting the scattered product data that sits across design, manufacturing, and operations systems inside the world\u2019s largest industrial companies.

The round was led by OTB Ventures, the London-headquartered firm that has become one of Europe\u2019s most active deep-tech growth investors with more than $350 million under management. DTCP Growth, IQT, Salesforce Ventures, and Thesiger Capital joined as new investors, alongside angel investor Christian Schulz. Existing backers HV Capital and Nauta Capital also participated, signaling continued confidence in a company that has quietly assembled an impressive roster of industrial customers.

The Problem No One Wants to Talk About

Founded in 2019 by Philipp Noll and Robert Goebel, SPREAD emerged from a frustration that any engineer at a major manufacturer would recognize: engineers spend roughly 70 percent of their time on manual data searches, hunting across PLM, CAD, ERP, and service tools just to ensure that a single component fits the bigger picture. The information exists, but it is trapped in siloed legacy systems that were never designed to talk to each other.

SPREAD\u2019s answer is its Engineering Information Model -- an AI-native ontology layer that sits on top of existing enterprise software and structures the chaos into what the company calls a continuous \u201CProduct Twin.\u201D Unlike a digital twin, which typically models physical behavior, SPREAD\u2019s Product Twin connects engineering, production, and service data in real time, creating a single source of truth across the entire product lifecycle.

\u201CThis is not just about better software, it is about competing at the speed these times demand,\u201D said co-founder Philipp Noll. \u201CGlobal manufacturers have spent decades building world-class products. They deserve an AI-native foundation that respects their engineering data and standards, and future-proofs the operational excellence that sets them apart.\u201D

Enterprise Traction Across Automotive, Aerospace, and Defense

The platform is now deployed in more than 100 enterprise environments, with customers that include Volkswagen, BMW, Mercedes, Rheinmetall, and Infineon. According to the company, deployments have delivered up to 30 percent faster development cycles and reduced engineering troubleshooting time by as much as 75 percent -- numbers that, if they hold at scale, represent significant cost savings in programs where a single vehicle platform can cost billions to develop.

Co-founder Robert Goebel emphasized the strategic importance of the Salesforce partnership in reaching new verticals. \u201CWorking with Salesforce gives us the reach to bring Engineering Intelligence to the industrial companies that need it most: the teams developing, operating, or servicing defense systems, vehicles, and industrial machinery,\u201D Goebel said. \u201CTogether, we are making sense of industrial data scattered across a sprawl of legacy systems with our AI-native data foundation that lets engineering, sales, and service teams decide and act with speed and confidence.\u201D

Why This Round Matters

The $30 million raise -- approximately 25 million euros -- arrives at a moment when Europe is increasingly vocal about AI sovereignty. While much of the continent\u2019s AI investment has flowed toward foundation models and consumer applications, SPREAD represents a different thesis: that the real value of AI in industry lies not in building bigger models but in making existing models useful by giving them access to structured, context-rich engineering data.

OTB Ventures, which focuses on enterprise automation and AI among its four core verticals, led the round as part of its broader bet on European deep-tech companies that can compete globally. The inclusion of IQT -- the strategic investment arm of the U.S. intelligence community -- and Salesforce Ventures adds both geopolitical and commercial weight to the investor syndicate.

The capital will be directed toward three priorities: international expansion beyond Europe, development of advanced AI agents that can act on engineering data autonomously, and deeper product data capabilities for the automotive, aerospace and defense, and industrial equipment sectors.

The Competitive Landscape

SPREAD operates in a space adjacent to established PLM vendors like Siemens Teamcenter, PTC Windchill, and Dassault Systemes, but it is not trying to replace them. Instead, the company positions itself as the connective tissue layer -- the AI-native middleware that makes decades of accumulated engineering data accessible and actionable without requiring manufacturers to rip and replace systems they have spent years configuring.

That positioning is both a strength and a risk. If the major PLM vendors build their own AI integration layers -- and Siemens, in particular, has been investing heavily in industrial AI -- SPREAD could find itself squeezed. But for now, the complexity of multi-vendor environments in large manufacturers creates a natural opening for a platform-agnostic approach.

What to Watch

The next twelve months will test whether SPREAD can translate its European automotive beachhead into a genuinely global industrial platform. The defense sector, where data fragmentation is acute and security requirements add another layer of complexity, could prove to be the company\u2019s most consequential growth vector. If SPREAD\u2019s Product Twin can handle classified environments alongside commercial ones, the addressable market expands dramatically. For now, with 100-plus enterprise deployments and a blue-chip investor syndicate, the Berlin startup has earned the right to make that case.