ENGINEERING
Custom AI Model Development
Computer-vision, yield-prediction, and prescription-generation models — trained on your data, owned by you.
Engagement shape
What this engagement looks like.
Custom AI engagements scoped to a defined model objective (e.g., 'detect powdery mildew on enrolled vineyards 14+ days before visual symptoms'). Includes data labeling, model training, evaluation, deployment, and MLOps. Models live in your environment — JMJ does not retain weights.
What's in scope
Scope.
- Problem scoping and success metrics
- Data labeling and curation
- Model training and evaluation
- Explainable AI (XAI) layer
- On-prem or edge deployment
- MLOps and retraining pipeline
What we ship
Deliverables.
- Trained production model
- Inference pipeline
- Evaluation report against agreed metrics
- MLOps tooling for retraining
Price band
$150K – $1.5M
Duration
8 – 24 weeks
Typical buyer
Head of agronomy, head of innovation, CTO
How we work
The JMJ AgriTech Method™
Four stages. Every engagement. No improvisation.
01
Assess
Discovery, audit, and roadmap. Bounded engagement, signed-off output.
02
Engineer
Architecture and build. Deployed in your environment, owned by you.
03
Integrate
Connect to your existing stack — equipment, ERP, finance, compliance.
04
Operate
Run the system to SLA, or transition cleanly to your in-house team.
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