AgriAI Trust

Farmer-controlled data. Rights-aware AI.

Trust is designed into sources, permissions, models and product language—not added after the field record becomes valuable.

Private by default

Raw field operations and outcomes stay tenant-private unless the customer chooses another purpose.

Separate purposes

Producing a field report and improving pooled models require separate, intelligible permissions.

Rights before use

Acquired does not mean publishable. Licence, consent and permitted use gate every pathway.

Challenge the result

Important metrics include a correction, feedback and escalation route.

THE AGRIAI TRUST LEDGER

The questions every live dataset and model must answer.

Where did it come from?Publisher, customer or sensor and stable source identifier

What exactly was acquired?File, API, table, product and version

Under what rights?Licence, contract and permitted product uses

What changed it?Transformation code and version

Did it enter model training?Training dataset, authorization and cutoff

Which model used it?Model version, hash and feature snapshot

How good is that model here?Validation cohort, baseline and calibration

Can the user challenge it?Correction, feedback and escalation route

CLEAN-ROOM SOURCE POLICY

Original work, governed evidence.

AgriAI allows original analysis, open-government data used within licence, contracted commercial data, customer-authorized farm data and peer-reviewed research used as evidence.

Competitor copy, screenshots, scraped articles, unclear-licence data and unapproved customer-data reuse are blocked from production workflows.

Canola Council of Canada content is hard-excluded from AgriAI editorial, retrieval, training and data pipelines.

Build your evidence layer

Start with the public picture. Add your field when you are ready.

Explore Atlas Request field access