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Ref: RDRMK20251223028
Descripción
Macedonian SME specialized in Enterprise Resource Planning (ERP) software seeks partners to develop a "Glass Box" Explainable AI (XAI) module. Unlike traditional "black box" AI, this solution will provide transparent reasoning for decisions within ERP workflows. The company is looking for universities, research centers, or ICT SMEs to join a consortium (e.g., for Eurostars or Horizon Europe) to further develop algorithms that combine high predictive accuracy with human-understandable explanation.
Title
Macedonian ERP developer seeks partners for "Explainable AI" (XAI) integration in business software under research funding programmes
Abstract
The company is an established software provider from North Macedonia with over 2,300 corporate clients and a team of 21 employees. They have successfully developed a comprehensive ERP solution that already utilizes Artificial Intelligence for user/product segmentation and inventory optimization.
The goal of the proposed R and D project is to overcome a major barrier in business AI: the lack of trust due to "black box" models. The company aims to develop a novel "Glass Box" approach that combines:
1. Seamless ERP Integration: Embedding AI directly into daily business operations/workflows.
2. Explainability (XAI): Revealing the reasoning behind each AI output (recommendation or prediction) to the user.
3. Performance: Achieving robust predictive accuracy that matches or exceeds opaque models.
The project aims to transform AI decision-support into a transparent tool where users understand why a specific inventory level is recommended or why a customer segment is targeted.
The company is looking for partners to collaborate on the algorithmic development, validation, and testing of this XAI framework within real-world business scenarios.
Advantages and innovation
The primary innovation lies in the shift from "Black Box" to "Glass Box" AI within a native ERP environment.
• Trust and Adoption: Current ERP-embedded AI modules often lack interpretability. By providing clear explanations, this solution increases user trust and adoption rates.
• Hybrid Performance: The solution targets a unique blend of advanced XAI and direct workflow integration, ensuring that transparency does not come at the cost of predictive accuracy.
• Market First: No competing solution currently offers this level of deep integration combined with explainable logic for SMEs, setting it apart from traditional ERPs (low AI) and standalone AI platforms (low integration).
Technical Specification or Expertise Sought
The company seeks partners with expertise in:
• Machine Learning algorithms, specifically Explainable AI (XAI) methodologies.
• Data semantics and predictive modeling.
• Validation of AI models in business environments.
Framework program
Business and innovation services
Call title and identifier
Enterprise Europe Network – Business and Innovation Services (EEN BIS)
Submission and evaluation scheme
Anticipated project budget
Coordinator required
Yes
Deadline for EoI 31 Mar 2026
Deadline of the call 31 Mar 2026
The goal of the proposed R and D project is to overcome a major barrier in business AI: the lack of trust due to "black box" models. The company aims to develop a novel "Glass Box" approach that combines:
1. Seamless ERP Integration: Embedding AI directly into daily business operations/workflows.
2. Explainability (XAI): Revealing the reasoning behind each AI output (recommendation or prediction) to the user.
3. Performance: Achieving robust predictive accuracy that matches or exceeds opaque models.
The project aims to transform AI decision-support into a transparent tool where users understand why a specific inventory level is recommended or why a customer segment is targeted.
The company is looking for partners to collaborate on the algorithmic development, validation, and testing of this XAI framework within real-world business scenarios.
Advantages and innovation
The primary innovation lies in the shift from "Black Box" to "Glass Box" AI within a native ERP environment.
• Trust and Adoption: Current ERP-embedded AI modules often lack interpretability. By providing clear explanations, this solution increases user trust and adoption rates.
• Hybrid Performance: The solution targets a unique blend of advanced XAI and direct workflow integration, ensuring that transparency does not come at the cost of predictive accuracy.
• Market First: No competing solution currently offers this level of deep integration combined with explainable logic for SMEs, setting it apart from traditional ERPs (low AI) and standalone AI platforms (low integration).
Technical Specification or Expertise Sought
The company seeks partners with expertise in:
• Machine Learning algorithms, specifically Explainable AI (XAI) methodologies.
• Data semantics and predictive modeling.
• Validation of AI models in business environments.
Framework program
Business and innovation services
Call title and identifier
Enterprise Europe Network – Business and Innovation Services (EEN BIS)
Submission and evaluation scheme
Anticipated project budget
Coordinator required
Yes
Deadline for EoI 31 Mar 2026
Deadline of the call 31 Mar 2026