Key Takeaways
- Orbem, a German‑based AI‑driven imaging company, has secured €55.5 million in Series B funding and opened a U.S. headquarters in Houston.
- Its core technology is an industrial‑grade MRI scanner originally deployed in poultry (over 200 million eggs scanned) and now being adapted for fresh produce such as watermelons and avocados.
- The system provides non‑destructive, high‑resolution internal imaging, enabling automatic detection of hidden defects like hollow heart or rot.
- Orbem sells the service as an operational‑expenditure (OpEx) model, charging a marginal fee per scanned pound, which lowers upfront capital barriers for packers.
- Transparent internal quality data allows producers to tier pricing, reduce shrinkage, and potentially build differentiated brands.
- First commercial watermelon scanners are live in Spain (JimboFresh); U.S. deployments are expected in early 2027, with broader adoption in late 2027–2028.
- By moving quality assessment inside the fruit, Orbem aims to bring greater transparency to the fresh‑produce supply chain and improve decision‑making for growers, packers, and retailers.
Background and Funding
Orbem began as a specialist in AI‑powered imaging for the poultry sector, where its technology proved capable of scanning massive volumes of eggs with high accuracy. The company’s success attracted significant investor confidence, culminating in a €55.5 million Series B round. With fresh capital in hand, Orbem established a U.S. headquarters in Houston, a logistics hub that CEO Pedro Gomez describes as strategically positioned for reaching the rest of the nation. This move signals the firm’s intent to translate its proven poultry‑egg platform into the fresh‑produce arena, beginning with watermelons and avocados.
From Poultry to Produce
Transitioning from the uniform shape of poultry eggs to the irregular geometry of fresh fruit presented a fresh set of engineering challenges. Gomez notes that while acknowledging that handling an avocado or watermelon differs from handling an egg, but stresses that the underlying automation principles remain comparable. Orbem therefore partners with established automation firms to customize conveyors and fixtures that accommodate a wide range of sizes and shapes, ensuring smooth passage through the scanning tunnel without damaging the produce.
Technological Adaptation
Once inside the system, each piece of fruit encounters a specialized scanner built on medical‑grade MRI technology, re‑engineered for industrial speed and durability. Gomez explains that the scanner captures a fine‑grained, high‑resolution image from the skin to the core in a fraction of a second. This capability allows Orbem to visualize internal structures that are invisible to the naked eye, turning what was once a hidden quality variable into measurable data.
Industrial MRI Technology
The MRI platform Orbem employs is not a novelty; it has already logged more than 200 million egg scans in poultry operations worldwide. Each scan refines the underlying AI models, making the system progressively better at distinguishing normal tissue from anomalies such as hollow heart, internal rot, or uneven ripening. By leveraging this large, growing data set, Orbem’s algorithms achieve high precision while maintaining the throughput required for modern packing lines.
Scanning Strategy
To avoid bottlenecks on high‑speed lines, Orbem calibrates its scanner for the worst‑case scenario: it always captures data as if processing the largest possible watermelon. When a smaller fruit passes through, the system simply records a smaller version of the same data set, preserving consistency without sacrificing speed. This approach ensures that the scanner’s performance remains stable across the natural size variability found in produce batches.
Operational Workflow
Gomez breaks the end‑to‑end process into three clear steps for packers: (1) Line Movement – conveyor belts transport fruit from point A to B; (2) The Big Tube – the produce enters the MRI scanner’s enclosure where raw data are collected; (3) The AI Decision – an onsite computer analyzes the images using pretrained models, then triggers mechanical sorting gates to route fruit into appropriate quality streams. The entire sequence operates autonomously, requiring minimal human intervention beyond routine maintenance.
Business Model and Pricing Flexibility
Rather than demanding a large upfront capital expenditure, Orbem offers its scanning service as an operational‑expense (OpEx) solution. Packers pay a modest fee per scanned pound, allowing them to adopt the technology incrementally and scale as ROI becomes evident. Importantly, the quality thresholds and grading parameters are set by the producer, not the technology vendor, giving growers control over how internal quality translates into market tiers and price points.
Transparency, Pricing, and Brand Differentiation
By revealing the true internal condition of each fruit, Orbem empowers packers to base pricing on verified quality rather than external appearance alone. Gomez highlights that this transparency can drive shrinkage down toward zero, as defective items are identified before they reach retail shelves. Moreover, producers who can certify the internal quality of every box may leverage that proof to create premium, differentiated brands, commanding higher prices and strengthening retailer relationships.
U.S. Rollout Timeline
While Orbem’s first commercial watermelon scanner is already operational in Spain with producer JimboFresh, the United States has yet to host a live installation. Gomez anticipates the first U.S. deployments in early 2027, followed by broader adoption in late 2027 and throughout 2028 as early users validate the system’s impact on quality and waste reduction. The staggered rollout mirrors the company’s strategy of refining the technology in European markets before scaling domestically.
Vision and Impact
For Gomez, who grew up in the Northeast of Mexico, bringing MRI‑based transparency to the avocado and fresh‑produce supply chain is both a professional mission and a personal commitment. He acknowledges that no single technology will solve every industry challenge, but believes that increased insight into internal fruit quality will enable smarter decisions across the value chain—from field to fork—ultimately fostering a more efficient, less wasteful, and more trustworthy fresh‑produce market.