Data Governance

AgFlow Intelligence operates under a formal data governance framework designed to ensure analytical integrity, transparency, and appropriate use of information.

Our governance model emphasizes source discipline, methodological consistency, and explicit use-case boundaries to support professional and institutional decision processes.

Data Sources
AgFlow Intelligence relies exclusively on publicly available, authoritative data sources, including but not limited to:
- Government agencies and official statistical bodies
- Regulatory and reporting authorities
- Market structure and positioning disclosures

Primary sources may include USDA, CFTC, and other recognized public institutions.
We do not incorporate proprietary price feeds, private order flow, or undisclosed third-party data.

Data Handling and Validation
All data used in AgFlow Intelligence materials is:
- Collected from identified, documented sources
- Reviewed for internal consistency and completeness
- Evaluated within defined temporal and methodological boundaries

Where applicable, reporting lags, revisions, and data release schedules are explicitly acknowledged to prevent misinterpretation.

Methodology Governance
Analytical methods are:
- Documented and applied consistently across reporting periods
- Designed to emphasize comparability, repeatability, and auditability
- Version-controlled to preserve historical integrity

Methodological changes, when required, are implemented deliberately and disclosed to maintain continuity and user trust.

Use-Case Boundaries
AgFlow Intelligence analysis is designed to support:
- Market condition assessment
- Governance review and escalation discipline
- Risk awareness and oversight

It is not designed for:
- Trade execution or signal generation
- Real-time decision automation
- Circumventing internal risk, compliance, or approval processes

Users are responsible for ensuring that AgFlow Intelligence materials are applied within their organization’s governance and compliance frameworks.

Independence and Integrity
AgFlow Intelligence maintains analytical independence by:
- Avoiding compensation tied to market outcomes or execution
- Separating information analysis from decision authority
- Publishing explicit disclosures and use limitations

Our data governance framework is intended to support disciplined interpretation, not reactive or speculative behavior.