External data intake
Automated collection through direct connectivity with suppliers' existing core systems, plus emails, documents, spreadsheets, ERP exports, and partner-specific formats.
Our Vision
Our Vision
From fragmented external inputs to usable food supply chain intelligence.
From outside data collection to usable intelligence.
The future of food commerce will not be powered by manually collecting PDFs, emails, system exports, and spreadsheets from every trading partner.
It will be powered by automated external data intake, AI-powered mapping, validation workflows, and usable data layers that allow companies to understand supplier risk, compliance, traceability, and transaction readiness in real time.
Riv Inc. is building toward that future.
Long-term vision
The automation layer for food supply chain data operations.
Cibus OS is designed to become the automation layer that collects external supplier and partner data and turns it into usable data for food supply chain transactions.
In the future, suppliers, manufacturers, distributors, and retailers should be able to continue using their own internal systems while Cibus OS automates the collection, mapping, validation, and secure exchange of the data required for trust, compliance, traceability, and transactions.
Cibus OS should work as a neutral automation and data layer that makes fragmented food supply chain data usable in real time.
Usable data operations
AI-powered mapping, validation, normalization, and monitoring that prepare external data for compliance, traceability, and commerce.
Cibus OS direction
An automated data operation layer for trust, compliance, and traceability.
Collecting data from suppliers' existing core systems, manufacturers, distributors, retailers, files, emails, and system exports.
Turning fragmented external inputs into structured data that teams and systems can actually use.
Making food compliance data easier to collect, validate, normalize, and update.
Helping companies monitor supplier risk when external data changes or becomes incomplete.
Mapping supplier-specific fields, files, and formats into standardized, usable data structures.
Supporting trusted sharing between trading partners and enterprise systems after data has been validated.
Keeping external data current instead of trapped in static files and manual workflows.
Preparing usable supplier data for safer, faster, more intelligent food commerce.
Building intelligence from data that used to be scattered outside the enterprise.
Next step