Data lineage
What observations, time periods, spatial resolution and verification methods support the answer?
- Source and location
- Timestamp and history
- Quality checks
- Permissioned context
Enterprise trust
Intelligence must
earn the right to act.
Enterprise AI needs traceable data, validated models and workflows that put accountable people in control. These are the questions we work through with every deployment.
Evaluation framework
Four layers of enterprise confidence.
Specific controls and contractual commitments are defined for each customer deployment and can be reviewed with Cropin’s team.
Model evidence
How was the model validated for this crop, geography, season and decision window?
- Validation scope
- Performance measures
- Uncertainty
- Monitoring
Human oversight
Who reviews a recommendation, approves an action and owns the operating outcome?
- Role-based review
- Approval points
- Exception handling
- Decision history
Enterprise deployment
How will the data and outputs connect to customer systems, access policies and governance?
- Integration design
- Data handling
- Operational support
- Contractual terms
Policies and diligence
Review the terms that govern your use.
Cropin publishes its privacy policy and legal terms. For deployment-specific security, privacy and model-governance documentation, contact the enterprise team.