At Metafoodx, we believe artificial intelligence should be used to improve lives, support sustainability, and operate with transparency. Our AI systems power critical tools for food service providers—from forecasting to food waste reduction—and we take seriously our responsibility to build technology that is safe, fair, and trustworthy.

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Our Core Principles

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Transparency

 

We design our AI systems to be explainable and understandable. Our models include confidence scores, reasoning summaries, and human-readable reporting. We ensure that stakeholders—from chefs to operators—can understand how AI is making decisions and take action accordingly.

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Fairness & Bias Mitigation

 

We actively work to reduce bias across our systems. Our models are trained on diverse, real-world data collected across different institutional environments. We regularly test for performance variations across food types, lighting conditions, and operational setups. Human-labeled QA and external validation partners help us maintain fairness and accuracy.

 

Human Oversight

 

AI should support—not replace—human decision-making. Our system allows users to override predictions, classifications, or recommendations at any time. These overrides are logged and reviewed to improve the model through feedback loops and retraining processes.

 

Data Privacy & Security

 

All data collected through our systems is encrypted in transit and at rest. Access is role-based and auditable. We follow best practices aligned with frameworks like NIST 800-53 and the NIST AI Risk Management Framework (AI RMF), and we are pursuing SOC 2 compliance. We never sell or share customer data with third parties.

 

Environmental Responsibility

 

We design our models to be lightweight and efficient. Training and inference run on cloud infrastructure optimized for energy efficiency. We track model training energy use and water impact, and we prioritize resource-sharing strategies to reduce our environmental footprint.

 

Accountability & Improvement

 

We are committed to continuous improvement through internal review and future third-party audits. We use external QA teams to validate performance and plan to publish independent impact assessments as we scale. If errors, bias, or safety issues arise, we respond quickly and transparently.

 

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Looking Ahead

 

AI in food service is still evolving, and we are committed to shaping its future responsibly. As Metafoodx grows, so will our investments in fairness, accountability, sustainability, and transparency.

 

For more information or to report concerns about any AI output, please contact us at support@metafoodx.com.