M&A

Source.ag acquires Optimal, London AI greenhouse control startup

October 9, 2026

AI & Data

M&A

Key Facts

Signal Type

M&A

Industry

AI & Data

Companies

Source.ag, Optimal, Agro Care, Founders Fund, Astanor Ventures

Date

October 9, 2026

What Happened

Source.ag, the Amsterdam-based AI platform for greenhouse growers, acquired Optimal, a London startup that built one of the first AI systems to autonomously control a commercial greenhouse. Optimal's AI directly manages heating, ventilation, lighting, CO₂, and irrigation through existing hardware, using proprietary physics and ML models to plan days ahead and re-optimize in real time. In a Dutch commercial-scale greenhouse, it delivered 13% more yield with 27% less energy than the benchmark grower.

Who Is Affected

Source.ag—the acquirer with 500+ greenhouses across 25 countries, supporting €2.5B of annual production and 13 of the world’s 25 largest high-tech growers. Optimal—the target, whose founder Dave Hunter joins Source as VP Autonomous Control, along with Optimal's engineering team. Agro Care, one of Europe's largest greenhouse tomato producers and a Source customer, plans to be among the first to use the autonomous control system.

Market Impact

  • The acquisition combines Source's crop monitoring and irrigation automation with Optimal's climate control, creating a closed-loop system that observes, predicts, and acts.
  • It addresses a global shortage of skilled growers, which limits greenhouse scalability—a critical issue as extreme weather and energy volatility increase the need for indoor food production.
  • Source has raised €50M from investors including Astanor Ventures and is backed by Founders Fund through Optimal. The combined platform is positioned to enable greenhouse deployment everywhere on earth.

What to Watch

The first autonomous deployments at Source customers in Europe and North America go live this winter. Source then plans to extend its AI suite to more crops, growing methods, and regions, potentially accelerating the adoption of physical AI in controlled-environment agriculture.

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