Sustaain provides an AI‑driven platform that ingests, cleans, and validates sustainability data from farm records, satellite imagery, and surveys to generate traceable, regulation‑compliant indicators for soft‑commodity supply chains. The system automates KPI extraction, document conversion, and geospatial risk assessment, delivering results through a centralized Traceability Hub for reporting, benchmarking, and risk management.
Funding
Funding not disclosed
Founders
Product
Problem
Operators of soft‑commodity supply chains lack reliable, standardized sustainability data, making it difficult to meet regulatory requirements such as the EU Deforestation Regulation (EUDR) and CSRD, and to assess environmental and social risks across origins.
Solution
Sustaain offers an AI‑driven platform that ingests, cleans, and qualifies sustainability data from diverse sources—including farm records, satellite imagery, and third‑party surveys—to produce traceable, compliant indicators. The system automates KPI extraction, document conversion, and geospatial validation, reducing manual effort and improving data accuracy. Built as modular engines, the platform supports use cases such as deforestation risk assessment, coffee plot detection, human‑rights monitoring, and comprehensive traceability reporting. Results are delivered through a centralized Traceability Hub and can be exported for regulatory reporting, benchmarking, and risk management. By combining generative AI, data‑science algorithms, and probabilistic modeling, Sustaain enables operators, traders, and downstream companies to demonstrate compliance and make data‑backed sustainability decisions at scale.
Target Audience
Primary customers are operators, traders, and downstream companies in the soft‑commodity sector (e.g., coffee, cocoa, palm oil) that need to meet EU sustainability regulations and improve supply‑chain transparency.
Features
- Automated KPI extraction that classifies and aligns metrics with CSRD, EUDR, and other reporting frameworks
- Document intelligence engine that converts unstructured farm data (Excel, CSV, PDFs) into clean, database‑ready formats
- Coffee plot detection using machine‑learning and GIS methods to validate land‑use and assess cultivation suitability
- Deforestation risk assessment leveraging satellite imagery and geolocation verification to generate compliant due‑diligence reports
- Human‑rights monitoring module that aggregates farmer and worker surveys with external datasets to flag labor violations
- Traceability Hub that consolidates commodity flow data, highlights gaps, and applies probabilistic modeling to strengthen chain‑of‑custody evidence
- End‑to‑end data engineering services for pipeline construction, governance, and industrialized data factory deployment