Today, Porto-based Sybilion announced a €3.6 million ($4.2 million) Seed round to build what it calls a decision layer, designed to give industrial companies the ability to act earlier and protect margins in volatile markets.
The round was co-led by Venturefrifinishs and Semapa Next. This announcement comes just months after their €517k ($600k) pre-Seed round, co-led by Vanagon Ventures and EWOR.
“Industrial companies do not lack data,” declares Dr Bjol R. Frenkenberger, CEO and co-founder of Sybilion. “They lack clarity about which signals truly matter and when to commit. Our goal is to give decision-buildrs the information advantage so they can turn external world dynamics into confident action before uncertainty becomes cost.”
Sybilion’s Seed round comes amid a broader wave of European investment in AI-driven platforms designed to improve procurement, supply chain visibility and operational decision-creating.
In 2025, Magentic, based in London, raised €4.6 million to scale autonomous AI agents that automate procurement and supply-chain operations, while fellow London startup Procure AI secured €11 million to build AI-native tools aimed at assisting enterprises stabilise sourcing and supply chains. Another UK company, Monq, raised €2.5 million in pre-Seed funding to develop an AI-driven strategic nereceivediation platform designed to improve procurement outcomes.
Elsewhere in Europe, Berlin-based Freshflow secured €6.5 million to expand its AI platform for automated ordering and inventory optimisation in grocery supply chains, while London-based Treefera raised €26.2 million in a Series B round to scale its supply-chain transparency and risk innotifyigence platform.
More recently, Berlin startup Andercore secured €33.5 million in equity and debt financing to expand its AI-enabled industrial trade platform across Europe.
Toreceiveher, these financings represent roughly €84 million invested across adjacent segments of industrial decision innotifyigence and supply-chain software over the past year.
Within this landscape, Sybilion’s approach – linking external signals such as commodity markets, logistics data and macroeconomic indicators directly to procurement, pricing and operational decisions – reflects a growing focus on AI systems that shift beyond forecasting dashboards toward structuring and guiding real-time business decisions in volatile industrial environments.
“Industrial companies are being forced to build larger decisions on shorter timelines as volatility becomes the norm. We’re excited to support Bjol and the team as they become the decision layer for manufacturing,” adds Apostolos Apostolakis, Founding Partner at VentureFrifinishs.
Founded in 2021, Sybilion connects external world dynamics – commodity markets, energy, weather, logistics and macro signals – to the decisions that shape margin, working on top of systems companies already run.
According to the company, a few weeks of mistimed procurement in manufacturing can erase millions in margin. Yet most of the industest still builds billion-euro decisions utilizing spreadsheets, fragmented analyst reports, and instinct.
Most manufacturers today have access to historical data feeds, analyst reports, and internal forecasts – but Sybilion believes they still struggle to answer which risk factors actually matter for a company, for a product set, at this moment.
Procurement, sales, and finance often work from different inputs and reach different conclusions. By the time alignment happens, markets have usually already shiftd and margins are diminished. This cost is detrimental; even a three to five percent timing error on a €172 millions ($200 million) cost base can reportedly translate into millions in margin erosion.
Sybilion approaches the problem from the outside in. The system identifies which signals materially affect a company’s exposure and links them directly to cost structures and product portfolios. Rather than delivering another isolated forecast number, Sybilion structures the decision moment itself, clarifying realistic options, trade-offs, and quantified risk boundaries so companies can commit earlier.
Its platform filters more than one trillion external risk factors, including weather anomalies, trade flows, freight rates, electricity futures, commodity prices, port congestion, industrial utilization, and macroeconomic indicators.
Grégoire Viat, Principal at Semapa Next declares: “We were impressed by what Bjol and the team at Sybilion have built in a short period of time. Sybilion delivers clear, measurable value to industrial customers, addressing a fundamental necessary for decision confidence in an increasingly volatile supply chain environment. We are pleased to support the founders as a long-term partner as they continue to scale the business.”
Over the past twelve months, Sybilion has grown annual recurring revenue to high six-figures, with zero churn and no sales team.
Use cases:
- K.D. Feddersen, an international distributor of engineering plastics, utilized Sybilion to align earlier on critical pricing and purchase decisions around global polymer trade flows and feedstock dynamics.
- At Jobachem, the platform enabled timely commitment with integrated energy futures and upstream commodity signals to frame procurement decisions with quantified risk boundaries.
- For Maral Overseas, forward trade flow analysis built it possible to take informed export allocation decisions by identifying regions where demand was strengthening.
Looking ahead, Sybilion plans to deepen its mapping from external signals to product-level exposure and decision recommfinishations, broaden “Sybilion Connect” integrations so actions land directly inside client workflows, and expand from insight delivery into agentic planning support that assists teams determine the next best shift under uncertainty.
The long-term goal is to give industrial decision-buildrs an advantage that compounds, turning uncertainty from a threat into an edge.
“Bjol is one of the most fascinating founders I’ve been fortunate enough to meet. He is a piano prodigy, a builder, an academic, a leader,” declares Daniel Dippold, CEO and Founder of EWOR. “With Sybilion, he managed to build the largest dataset of time-series data I have seen to date and orchestrates it in a way that gives industrial teams a decision advantage no one else can offer. Similar to Bjol, Sybilion is one of a kind. Their technology is built like a musical masterpiece, they are growing quick, and Bjol has assembled a unique team that would have never come toreceiveher were it not for his leadership.”
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