Our Team

Agronomists who know what a farm actually needs, paired with engineers who know how to build it.

Dr. Sarah Okonkwo

Johnbosco Onugwu

CEO & Co-Founder

Agronomist with 12 years in commercial crop research and field operations. Former research lead at CGIAR, where he managed multi-country precision farming trials across Sub-Saharan Africa and Southeast Asia. Johnbosco founded CropNexa after recognizing that the data needed to revolutionize farm decision-making already existed — it just wasn't being turned into action fast enough.

Marcus Tran

Sarah Okonkwo

CTO & Co-Founder

Machine learning engineer with deep expertise in computer vision and edge computing. Previously led the perception systems team at an autonomous vehicle startup, building real-time CNN pipelines for safety-critical environments. Sarah applies that same reliability standard to CropNexa's field-level anomaly detection — because in agriculture, a missed alert has real consequences.

Our Mission

Built by People Who've Walked the Field.

CropNexa was founded by agronomists and AI engineers who saw the same problem from different angles — and decided the only way to fix it was to build the technology themselves.

We Are Hiring

We're building a team of people who care about agriculture, not just technology.

Agronomy AI Researcher

Help us refine our spectral signature detection models across new crop types.

Apply Now →

Field Solutions Engineer

Work directly with our commercial partners to deploy hardware and integrate APIs.

Apply Now →

Full-Stack Developer

Build the next generation of our alerting dashboard and mobile applications.

Apply Now →
CropNexa sensor node deployed in commercial field

The CropNexa Standard

We Hold Our Technology to the Same Standard as a Field Agronomist.

A good agronomist doesn't just report what they see — they anticipate, prioritize, and recommend. That's exactly what CropNexa does, at a scale no human team can match. Our sensor hardware is ruggedized for dust, moisture, and harsh field environments. Our AI is trained on real farm outcomes, not just lab datasets.

The team behind CropNexa has combined experience spanning crop research in Sub-Saharan Africa, autonomous vehicle perception systems, and large-scale commercial farm operations — because solving this problem requires understanding both sides of the field gate.