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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Eight startups selected from more than 150 entries were scheduled to compete at the 2018 World Agri-Tech Pitch Day and Radicle Challenge in San Francisco. Each finalist was allotted a 15-minute presentation for investors and agribusiness experts, with a $250,000 investment from Radicle Growth announced as the prize. The winner was due to be announced March 20, 2018, and present at the summit’s Technology Showcase on March 21.
This is a historical account of the event held March 19–21, 2018—not a list of finalists for the current World Agri-Tech Innovation Summit. The contemporary report is available from Successful Farming.
How Pitch Day fit into the 2018 summit
World Agri-Tech Pitch Day was the startup competition within the broader World Agri-Tech Innovation Summit. The event took place in San Francisco during the March 19–21 summit. Its Radicle Challenge format paired the eight finalist pitches with a potential seed-stage investment from Radicle Growth, described at the time as an ag-tech acceleration fund.
The schedule called for the winner to be named on March 20. That company would then appear before the wider summit audience at the Technology Showcase on March 21. The announcement of a $250,000 investment was a proposed award at the time; the article does not establish the eventual investment instrument, closing date, or whether the full amount was funded.
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Four of the eight finalists were international, which the article described as 50% of the field. The cohort spanned biological innovation, farm hardware, software, robotics, logistics and livestock systems rather than representing a single precision-crop niche.
The eight finalists at a glance
| Startup | Country | Sector | Core problem | Technology or model | Likely buyer |
|---|---|---|---|---|---|
| BeeHero | Israel | Pollination and bee health | Weak colonies and inconsistent pollination | Data-driven hive and pollination monitoring | Beekeepers and growers |
| eggXYt | Israel | Poultry genetics and welfare | Incubating and culling male chicks | Early embryo-sex identification | Hatcheries and poultry producers |
| HerdDogg | United States | Livestock monitoring | Late or incomplete detection of animal-health problems | Smart tags sending biometric and behavior data to the cloud | Livestock operators |
| RootWave | United Kingdom | Weed control | Dependence on chemical and mechanical weed control | Electrical weed-killing equipment | Arable, vegetable and fruit growers |
| Sollum | Canada | Controlled-environment agriculture | Lighting that does not match crop needs | Optimized greenhouse lighting | Greenhouse and breeding operations |
| Tortuga | United States | Farm robotics | Labor and production costs in fresh produce | Robotics-as-a-Service | Fresh-produce farms |
| TradeLanes | United States | Commodity logistics | Fragmented trade documentation | Digital trade room and automated documents | Commodity traders, shippers and counterparties |
| Vence Corp | United States | Livestock management | Cost and labor demands of physical fencing | IoT and AI for virtual boundaries and monitoring | Ranchers and livestock operators |
What each startup was pitching
BeeHero — pollination data for beekeepers and growers
Israel-based BeeHero focused on commercial pollination and bee health. Its proposition was to help beekeepers maintain stronger colonies and help growers obtain more reliable pollination. The 2018 article reported the company’s claim that its technology could increase farm yields by at least 15%.
That percentage was a company-related claim, not an independently established result for every crop or farm. The investment case would depend on whether better hive management translated into repeatable value after accounting for monitoring costs, crop differences and weather. BeeHero’s site listed at the time was beehero.com.
eggXYt — identifying poultry sex before incubation
Israeli startup eggXYt was developing a way to identify an embryo’s sex immediately after an egg was laid. The intended outcome was to avoid incubating male chicks that would otherwise be culled, eliminating the associated 21-day incubation period and addressing a practice affecting billions of male chicks annually, according to the pitch description.
The concept still faced demanding technical and commercial questions: accuracy at hatchery speed, regulatory treatment, integration with existing breeding systems and proof that animal-welfare benefits persisted at commercial scale. The description established a proposed solution, not completed deployment or regulatory approval. The company URL listed in the article was eggxyt.com.
HerdDogg — real-time livestock biometrics
HerdDogg, from the United States, proposed smart tags that transmit individual-animal biometric and behavior data to a cloud platform in real time. The intended customer benefit was earlier insight into health issues, improved farm efficiency and possible savings for producers.
The article did not state the tags’ sensors, battery life, connectivity requirements, price, validation population or documented producer results. Those details are central to the economics because a livestock operator must weigh hardware replacement, network coverage, data subscriptions and labor savings. The listed company site was herddogg.com.
RootWave — electrical weed control
United Kingdom-based RootWave targeted nonchemical weed control. Its equipment applies electricity to kill weeds, with cereal, vegetable and fruit crops named as target markets. The pitch was aimed at reducing reliance on herbicides and mechanical cultivation.
Commercial adoption would turn on field speed, energy consumption, crop selectivity, soil and moisture conditions, equipment cost and performance relative to existing herbicide programs or cultivators. The 2018 report did not provide comparative trial results or a farm-level payback period. RootWave’s listed URL was rootwave.com.
Sollum — programmable greenhouse lighting
Canadian company Sollum proposed creating optimized lighting conditions for greenhouses and breeding farms. Its claimed benefit was better yield and efficiency by matching light conditions more closely to production goals.
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“Optimal” lighting is not a universal setting: outcomes vary with crop and cultivar, photoperiod, greenhouse design, climate, electricity prices and utility incentives. Investors would need evidence separating lighting effects from other growing changes, along with capital and operating-cost assumptions. The company URL listed was sollumtechnologies.com.
Tortuga — robotics sold as a service
U.S. startup Tortuga focused on fresh-produce farms and planned a Robotics-as-a-Service model rather than requiring every grower to buy a robot outright. The article reported Tortuga’s expectation that its systems could reduce costs by 20% and double profitability.
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Those were ambitious projected outcomes, not demonstrated results established by the article. Their meaning would depend on crop, task, acreage, labor availability, service fees, uptime and the assumptions used to calculate profitability. A service model can lower upfront capital needs, but it also makes the provider responsible for field support, utilization and maintenance. Tortuga’s listed site was tortugaagtech.com.
TradeLanes — a digital room for commodity documents
TradeLanes, based in the United States, marketed a digital trade room that automatically generates and coordinates documentation for physical commodity transactions. The proposed “single source of truth” was intended to reduce friction at shipment handoffs and improve efficiency, accuracy and cost control.
The article did not specify supported commodities, jurisdictions, document standards, counterparties or links to enterprise systems. Those integration details determine whether a documentation platform can scale beyond a controlled pilot. Its listed URL was tradelanes.co.
Rank #4
Vence Corp — digitally managed livestock boundaries
Vence Corp proposed using the Internet of Things and artificial intelligence to reduce reliance on physical fencing and manual labor while adding health detection and real-time monitoring. Its core idea was a virtual or digitally managed livestock boundary.
A practical deployment would require reliable connectivity, durable and maintainable collars or tags, animal training, welfare safeguards, terrain tolerance and a safe response when equipment or power fails. The 2018 article did not establish those operating limits or the applicable regulatory framework. Vence’s listed URL was vence.io.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why the cohort was notable
Biology and animal welfare
BeeHero and eggXYt addressed biological bottlenecks rather than simply adding another farm-management dashboard. BeeHero worked at the pollinator–crop interface; eggXYt targeted genetics, hatchery economics and animal welfare. Both required evidence across biological systems that vary by species, cultivar, facility and operating practice.
Livestock intelligence
HerdDogg and Vence both depended on turning animal-level data into management decisions. Their products would be judged not only by sensor accuracy but also by whether a rancher can act on an alert, maintain the hardware and continue operating when connectivity is intermittent.
Lower-input production
RootWave sought a nonchemical weed-control route, while Sollum aimed to make controlled-environment lighting more responsive. One faces energy and field-condition constraints; the other faces electricity economics and crop-specific biology. Neither can be evaluated with a single universal yield or savings figure.
Automation and infrastructure
Tortuga addressed labor through a service-based robotics model. TradeLanes addressed the paperwork and coordination layer of commodity movement. These businesses sell to different decision-makers and have different scaling requirements: field service and machine utilization for Tortuga, interoperability and counterparty adoption for TradeLanes.
Claims versus evidence
The original 2018 coverage was a preview of startup pitches. It reported company descriptions and projections, not independent technical validation, audited financial results or a complete customer record.
| Statement in the 2018 coverage | How to read it |
|---|---|
| BeeHero could increase yields by at least 15% | Company-related claim; not a universal or independently verified result in the article |
| Tortuga could cut costs by 20% and double profitability | Projected outcome; the article does not provide crop, labor, acreage or pilot assumptions |
| eggXYt could avoid male-chick culling | Intended technical and welfare outcome; deployment, approval and hatchery-scale proof were not established |
| Winner to receive $250,000 | Announced prize; the article does not prove that an investment closed or identify its terms |
What happened after the pitches?
The source confirms the planned March 20 winner announcement and March 21 Technology Showcase appearance, but it does not provide a complete post-event account. On that evidence alone, it would be inaccurate to state which company ultimately won, that the $250,000 investment closed, or that any finalist’s performance claims were later validated.
Company names, websites, ownership, products and operating status may also have changed since 2018. The eight URLs above are the sites listed with the original article, not a guarantee that each company remains active or independent today. Readers assessing a current investment or partnership should verify present status separately.
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- Separate a compelling problem from a deployable product. Pollination, labor, weeds, animal welfare and trade paperwork are meaningful problems, but each requires a different installation and approval path.
- Map the paying customer. The buyer may be a beekeeper, grower, hatchery, rancher, greenhouse operator, produce farm, trader or shipper—not necessarily the person who uses the product daily.
- Price the full system. Hardware, connectivity, cloud fees, maintenance, labor changes, energy use and training can determine payback more than the headline feature.
- Match evidence to the claim. A company objective, a pilot result, an independent trial and commercial customer evidence are different levels of proof.
- Plan for failure and regulation. Virtual fencing, animal monitoring, gene-related poultry applications, electrical weed control and automated trade documents all create safety, welfare, data or compliance risks that must be managed before scale.
- Expect different capital timelines. Biological products and regulated systems may require lengthy validation, while software platforms may scale faster but depend on integrations and network effects.
The 2018 competition therefore offered more than eight similar pitches: it showed how varied the financing, evidence and adoption hurdles can be across ag-tech.
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