Skip to content
Home / Canonical Retail Platform Powered by AI

Canonical Retail Platform Powered by AI

The Katalist Platform project fits into the context of a rapidly evolving retail sector, characterized by the need for integration between different systems and a growing demand for technological solutions that enable agility and operational efficiency. The purpose of the project is to develop a robust platform that simplifies systems integration, reduces costs, and accelerates time-to-market, allowing retailers to dynamically adapt to market changes and consumer behavior. If the project is successful, the Katalist Platform will enable centralized and automated management of the demanding retail ecosystem, including an endpoint generation engine based on a canonical data model, a data integration engine in different formats, and automatic mapping and transformation between different data structures, all of which are revolutionary compared to the current state of the art. However, the development of a solution such as the one the company proposes to achieve within the scope of this project involves significant technical challenges, from the need to guarantee the efficiency of the platform’s engines, data security, scalability, maintaining consistency in asynchronous operations and the complexity of integrating different technologies cohesively.

Main Results Expected

  • More than 50 endpoints generated automatically
  • Over 5 complex data mappings generated and used
  • Integration of 5 different data formats
  • Automatic recovery of more than 30% of transaction errors (an improvement of +10% over current solutions)
  • More than 5 users of the integrated Katalist Platform

Project Organization and Structure

Canonical Retail Platform Powered by AI is structured around nine core activities, combining industrial research and experimental development:

  1. Project Management– Monitoring progress, deliverables, risks, and alignment with project objectives.
  2. Requirements & Market Study– Analysis of current technologies, retail and iPaaS markets, competitors, use cases, and functional requirement definitions.
  3. System Architecture & Technical Specifications– Design of the solution’s architecture and high-level technical specifications.
  4. Endpoint Generation Engine Based on Retail Canonical Data Model Development– Development and testing of the AI-powered endpoint generation engine through a canonical retail data model, ensuring compatibility with existing endpoints.
  5. Integration Engine Development – Development and testing of the integration engine to support multiple data formats and volumes.
  6. Error Recovery System Development– Development and testing of the transaction error recovery system.
  7. Test and validation of the various developments integrated– Specification and validation of the integrated developments in a laboratory setting, including prototype creation and result validation.
  8. Test and validation of the various developments integrated in a representative environment– Specification and validation of the integrated developments in a real-world representative environment, with final solution validation and preparation for commercial application.
  9. Dissemination and promotion of R&D results– Sharing outcomes through publications, conferences, and industry engagement initiatives.

Throughout the project, continuous collaboration between technical and academic teams ensures a balance between scientific innovation and real-world applicability.