TARANIS

Ofir Schlam, Shahar Geva, and Aviv Sender founded Taranis in 2015 with a straightforward but technically difficult premise: what if farmers could see problems in their fields before those problems became disasters?

The three founders came from technology and agriculture backgrounds and set up operations between Tel Aviv and the US agricultural heartland — specifically Champaign, Illinois, home to the University of Illinois's legendary agriculture programs. Israel is an unusual place to build a crop monitoring company, given that it has very little large-scale commercial farming.

But it's the right place to build an AI and computer vision company, given the density of technical talent and military-grade imaging expertise.

They started by developing ultra-high-resolution aerial imaging — using both manned aircraft and drones — that could capture fields at a resolution of one millimeter per pixel. At that level of detail, you're not looking at the field from above.

You're basically reading individual leaves. The AI layer then analyzes those images to detect the early signatures of dozens of different crop threats, from fungal infections to insect damage to potassium deficiency.

Taranis sells subscription access to its field intelligence platform — essentially a combination of recurring aerial surveys and AI-powered analysis. A farm subscribes, Taranis arranges flights over the fields at regular intervals during the growing season, and the platform generates reports on what it finds: where disease pressure is building, which sections need treatment, which can be left alone.

The value proposition to the farmer is clear: catch problems early and you can treat them surgically — a targeted spray over 10% of the field rather than a blanket application across 100% of it. That reduces chemical costs, reduces crop damage, and improves yield.

Taranis charges for the intelligence layer that makes that possible.

The model works best at scale — large row crop operations across thousands of acres, where the cost of surveillance is small relative to the crop value at stake.

Taranis Core is the main field monitoring platform. It combines ultra-high-resolution aerial imagery (captured by aircraft or drones at sub-millimeter resolution) with AI-powered analysis to identify crop threats at the individual leaf level.

Subscribers get regular flight reports, threat maps, and treatment recommendations through the platform interface.

The AI models at the heart of Taranis have been trained on millions of tagged field images across dozens of crop types and disease categories. The more fields Taranis surveys, the better the models get at distinguishing between, say, early soybean rust and a nutrient deficiency that looks superficially similar.

That data flywheel is a genuine competitive advantage.

The platform also integrates with farm management software, allowing the field intelligence data from Taranis to flow into the broader operational systems farmers already use for planting, harvesting, and logistics.

Taranis expanded geographically faster than most agtech startups. Within a few years of founding, they had operations in the United States, Brazil, Argentina, and Eastern Europe — targeting regions with large-scale commercial farming where the economic case for precision agronomics is strongest.

They partnered with agricultural input companies (seed, pesticide, and fertilizer suppliers) who saw Taranis's field intelligence data as a way to give their customers better recommendations — and, in turn, sell the right products at the right time. Input companies have the distribution relationships with farmers.

Taranis has the data. That partnership model let Taranis scale without having to build its own farmer sales force from scratch.

The Baidu investment in 2019 opened the door to the Chinese agricultural market — one of the world's largest and most challenging — where precision farming technology was being adopted rapidly by large state-owned and corporate farm operations.

Taranis faces the fundamental challenge of all precision agriculture companies: farmer adoption. The average commercial farmer in the US or Brazil is not a technology enthusiast.

They are risk-averse, skeptical of new tools, and have been burned before by agtech promises that didn't survive contact with a real growing season.

Convincing farmers that spending money on aerial surveillance will save them more than it costs requires years of demonstrated ROI — not just case studies, but data from their specific fields, crops, and conditions. This is slow.

And it requires Taranis to maintain a high-touch relationship with customers who are busy running complex operations.

There is also increasing competition from satellite-based monitoring companies — including Planet Labs and others — that can offer continuous field surveillance without the cost and logistics of aircraft and drones. Satellite resolution is improving fast.

As satellite imagery approaches the quality of aerial survey data, the cost structure of satellite monitoring becomes a serious competitive pressure.

Baidu Ventures led the $30 million Series B in 2019 — the most notable funding event in Taranis's history and an unusual crossover between Chinese tech capital and Israeli agtech. Baidu's investment brought both capital and a foothold in the Chinese agricultural market, where large commercial operations were beginning to adopt precision farming technology at scale.

Vertex Ventures, a multi-geography VC with offices in Israel, Singapore, and the US, was an early backer. Innovation Endeavors, the venture fund backed by former Google CEO Eric Schmidt, also participated — consistent with Schmidt's long-running interest in artificial intelligence applications in physical industries.

The combination of Israeli deep tech investors and global strategic backers gave Taranis unusual geographic reach in its early years.