Nutrad provides AI-enabled supply chain software that facilitates real-time data mapping and validation between brands, distributors, and retailers, ensuring accurate and consistent product information. This solution eliminates manual data entry errors and enhances operational efficiency, allowing businesses to manage unlimited trade connections while reducing costs and improving data quality.
Funding
Funding not disclosed
Founders
Product
Problem
Sharing and updating product information across trade channels relies on outdated tools or manual processes that are error-prone, costly, and time-consuming. Trade partners often receive inaccurate or inconsistent product information, limiting the number of trade partners an organization can effectively manage and leading to increased fines and customer returns.
Solution
Nutrad offers an AI-enabled SaaS platform that facilitates real-time data mapping and validation between brands, distributors, and retailers, ensuring accurate and consistent product information. The platform provides real-time translation and mapping to trade partner schemas, real-time data validation to industry and regulatory standards, and direct integration with existing systems and data sources. Nutrad's bi-directional data flow enables visibility to recall status and other data anomalies, while continuous learning improves data quality with trade partners. This solution enhances operational efficiency, enabling businesses to manage unlimited trade connections while reducing costs and improving data quality.
Target Audience
Nutrad's primary customers are brands, distributors, and retailers across various industries seeking to streamline product information sharing and improve data quality across their supply chains.
Features
- Real-time translation and mapping to trade partner schemas for consistent product information.
- Real-time data validation against industry and regulatory standards (e.g., GS1, FDA).
- Direct integration with existing systems and data sources, including PIM solutions.
- Bi-directional data flow for visibility into recall status and data anomalies.
- Continuous learning to improve data quality with trade partners.
- AI/ML-powered data mapping and validation.