Public Funding
Public Funding & Support
InCycling is conducting a publicly supported research and development project focused on asynchronous, multimodal AI for matching surplus chemicals and industrial resources with suitable demand.
Berlin Research Project
Multimodal AI System for Industrial Surplus Utilisation
The Project
Connecting complex industrial information with relevant demand.
The project is developing an ERP-near, AI-supported system that brings together information relating to chemical composition, material properties, process conditions and application contexts. The objective is to support the structured identification and assessment of suitable buyers or alternative applications for surplus industrial materials.
Objective
Develop and validate an ERP-integrated, AI-supported system for identifying, assessing and matching surplus chemicals and other product- and process-related industrial resources.
Research Focus
Research an asynchronous, multimodal matching approach capable of combining heterogeneous industrial information while accounting for technical, process-related and regulatory requirements.
Expected Result
Create a validated, modular AI matching system that brings together heterogeneous industrial information and is integrated as a prototype into an ERP-near platform.
Industrial Relevance
From fragmented information to better industrial decisions.
Inputs
Make complex information usable
Bring together material, process, application and regulatory information that is currently spread across different systems and documents.
Decisions
Support relevant matching decisions
Provide structured decision support for identifying potentially suitable buyers and alternative applications.
Outcomes
Strengthen industrial circularity
Improve the conditions under which usable surplus materials can remain in productive value chains.
Funding, Programmes & Ecosystem Support
Proudly supported by leading AI accelerator programs and industry networks
