How a Former Mobile Exec Is Building an Agricultural Data Infrastructure for a Billion-Dollar Future

Entrepreneur founder Calvin Cai is standardizing agri-data to help banks, farmers, and governments make smarter decisions.

NEW YORK, NY, UNITED STATES, July 30, 2025 /EINPresswire.com/ -- Calvin Cai once led mobile expansion across Southeast Asia, building high-velocity distribution platforms for app developers and advertisers. Today, his focus is no longer on pixels — but on plants.

As the founder of Beijing Horizon Data Technology, Cai is now building something few tech entrepreneurs are thinking about: a national-scale agricultural data infrastructure. While AgTech headlines often go to drones and autonomous tractors, Horizon Data’s work is less visible but arguably more fundamental — it’s helping define what agricultural intelligence actually means. “The future of food is a data problem before it’s a technology problem,” Cai says. “You can’t optimize what you can’t measure.”

FROM DEVICES TO DATASETS
Cai’s team has quietly mapped over 16 million acres of farmland across China, collecting geospatial, meteorological, and yield-based information through a combination of satellite imaging, edge devices, and institutional partnerships.

But unlike startups selling sensors or analytics dashboards, Horizon Data focuses on building the “data rails” — the underlying systems that financial institutions, insurance providers, agri-corporates, and government agencies can plug into.

“In any developed industry — finance, logistics, manufacturing — you eventually get to a stage where data becomes the utility layer,” he explains. “That’s where agriculture is heading.”

WHY THIS MATTERS: FRAGMENTATION AND CLIMATE VOLATILITY
China — and much of the Global South — suffers from deeply fragmented land ownership, limited field traceability, and inconsistent production tracking. Climate volatility has only made forecasting more complex.

Horizon Data’s strategy is to normalize, standardize, and structure messy, localized agricultural records into machine-readable assets. Its internal tools integrate satellite data, agricultural machinery operation records, planting records, and weather patterns to build live profiles of regions and farming clusters.

This allows regional stakeholders — from crop buyers to banks to insurance carriers — to make better decisions:
1. Which areas are the most intensive for planting operations?
2. Where should subsidies be targeted?
3. What is the true productivity of a given crop zone?

THE COMPETITIVE EDGE: INFRASTRUCTURE VS. INTERFACES
While many AgTech companies compete on UI and product experience, Horizon competes on data completeness and credibility. “We’re not trying to be the best dashboard — we’re trying to be the best system behind the dashboard,” Cai says.

This back-end orientation has made Horizon the data partner of choice for major Chinese agri-finance players, policy pilot zones, and agri-industrial zones looking to digitize risk models.

Cai compares it to how Stripe quietly became the infrastructure behind online payments:
“You don’t need to see us. You just need to trust that what we connect is clean, accurate, and reliable.”

FFROM FOUNDING TO ECOSYSTEM BUILDING
What makes Cai’s transition even more striking is that he has no background in agriculture. His previous ventures were in mobile advertising and offline distribution. What he brings, however, is an acute sense of platform design and ecosystem scaling.

Rather than chasing B2C monetization or short-term contracts, Horizon focuses on multi-stakeholder utility — making data usable for banks, farmers, logistics, insurers, and local governments.

The company has also begun exploring data-as-a-service (DaaS) models, offering analytics APIs and regional intelligence layers to enterprise clients.

INFRASTRUCTURE AS A LONG GAME
Cai is under no illusions about short-term wins. Agricultural data infrastructure, like most utility layers, is capital-intensive, politically complex, and highly fragmented in the early stages.

But the long-term prize is immense:
“Whoever standardizes agricultural data at scale doesn’t just make money — they shape how entire food systems function,” he says.

As the world faces climate-driven food uncertainty, Cai sees a future where data becomes the bridge between policy, productivity, and resilience.

His job? To lay the groundwork — one invisible layer at a time.

Jemma Wu
Asian Creative Foundation
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