Our Farming Technology

Ask ten people what “autonomy” means for a piece of farm equipment, and you'll get ten different answers. For most of the industry, it means solving one narrow task well: follow a line, avoid a fence post, stop for an obstacle. At Mojow, we started from a different question. What would it actually take for a machine to operate the way an experienced farmer does? From the moment it leaves the yard to the moment it returns, across every task and obstacle in between.

The answer is EYEBOX™: a box full of eyes and the perception system behind it, built to bring an expert-level judgment to autonomous farm equipment.

12

SPECIALIST AI APPLICATIONS

3M+

ANNOTATED TRAINING FRAMES

50M+

TESTING & EVAL FRAMES

5 Years

OF FIELD OPERATION DATA

A box full of eyes

EYEBOX™ is an integrated hardware and software platform. It's not just a single sensor bolted onto a machine, but a full sensing suite working together. It combines LiDAR, cameras, radar, microphones, GNSS, IMU, and CAN bus data, collected simultaneously from multiple viewpoints around the machine. That sensor suite streams multiple gigabytes of data per second into Mojow's perception applications, giving the system a continuous, high resolution picture of everything happening around it.

It's this breadth of sensing (sight, sound, position, and motion), that lets EYEBOX™ interpret a working environment the way a person would: not from a single camera angle, but from full situational awareness.

Why we build custom models, not generic ones

It may seem that it would be faster to take an open-source perception model, tune it a little, and call it done. However, in our experience, that is how you end up with a system that works 80% of the time and fails miserably for the rest of the 20%. More often than not, it's the edge case that causes real damage and risk.

Mojow takes the slower path on purpose. For every perception problem, such as detecting a rock pile, following a field boundary, or spotting a person in a work zone, we develop a custom, proprietary model that targets the specific problem directly and is built to solve it fully, not approximately. Every one of these challenges gets treated as its own expert-level problem, because on a working farm, “good enough most of the time” is simply not good enough.

Many specialist applications, one system

That philosophy is why EYEBOX™ isn't just one model - it's many, each built for a specific job, working together as a single perception system. Deployed applications include:

● Field boundary and crop row detection

● Obstacle detection

● Road driving perception

● Rock detection

● Implement identification (patent-approved)

● Human detection

● Yard navigation

Each of these runs as a dedicated, purpose-built application rather than a single generalized model asked to do everything at once, which is exactly how a system stays robust and real-time under the conditions a farm actually presents.

The data behind the judgment

None of this works without a lot of carefully built data. Mojow's models are trained on more than 3 million annotated frames and validated against more than 50 million targeted testing and evaluation frames, all produced by a dedicated 10-person annotation team working through a two-level quality review process.

That data comes from five years of real field operations spanning complete farming lifecycles, with specialized datasets covering rural roads, field boundaries, farm implements, crops, obstacles, and farm infrastructure. It's the same real-farm, real-farmer approach behind everything Mojow builds - training data drawn from actual working conditions.

Yard-to-Yard Autonomy

This is where Mojow's approach differs most from the rest of the industry. Rather than solving one isolated task, such as guidance down a single pass, we're building toward what we call Yard-to-Yard Autonomy: covering the complete farming lifecycle, from equipment preparation through the field work itself, to post harvest operations.

It's a harder problem on purpose. A machine that only performs well mid-field but can't safely navigate the yard, the road, or the transitions in between, isn't autonomous in any way that matters to a farmer's actual day.

Built for OEMs and for the people behind the wheel

EYEBOX™ is built for two audiences at once. For OEMs, it's a perception platform ready for integration partnerships. Expert-level models built to match or exceed experienced human operator performance, without asking to reinvent your existing equipment. For farmers, it's a system designed to interpret context and execute the tasks they direct, while keeping them in control of the operation, not replaced by it.

That's the outcome we're building toward: autonomy that behaves less like a narrow automation feature and more like a second set of expert eyes on the machine that is trained on real farms, for the real work of running one.

To learn more about EYEBOX™ and the technology behind it, visit mojow.ai/technology.