Explore the future of supply chain with AI

From requirements management to the best logistical path: orchestrate a truly flexible Supply Chain

Finding the best logistics path is no longer just about optimizing costs: it's about constantly balancing customer service, flexibility and sustainable logistics. Starting from the management of needs, the Supply Chain can rely on digitalization, traceability, traceability, workflow automation and AI to choose, at any moment, the most relevant scenario: right site, good transport, good stock level.

Supply Chain AI Chatbots: From Data to Action in One Question

New Supply Chain AI chatbots are no longer just answering questions: they connect to systems, understand business language, and trigger concrete workflows (resupply, traceability, delay management). They become real operational co-pilots in the service of digitalization, inventory optimization and sustainable logistics. The real question for organizations is no longer “do we need an AI chatbot?” , but what action-oriented use case should one start with to free up time for teams.

Automating product recognition: a foundation for a reliable and flexible Supply Chain

Automating product recognition (bar codes, RFID, RFID, RFID, computer vision, AI) is not just “modernizing” the warehouse.

360° Supply Chain Control Tower: from visibility to action

The 360° Supply Chain Control Tower makes it possible to move from fragmented visibility to real-time management of logistics flows, stocks and partners. By combining unified data, AI, workflow automation and a no-code platform, it strengthens customer service, inventory optimization and sustainable logistics.

Forecasting and planning: the new driver of supply chain performance

In a context of volatile demand and growing cost pressure, forecasting and planning have become a key performance lever for the Supply Chain. Digitalization, AI, workflow automation and no-code tools help improve forecast accuracy, optimize inventory, secure logistics flows and increase flexibility, while supporting sustainable logistics objectives.

AI, a new performance driver for the Supply Chain

AI is revolutionizing the supply chain by making flow management more agile, predictive and sustainable. It makes it possible to optimize stocks, automate operations and improve the accuracy of forecasts, while strengthening the overall performance of businesses.

OpenAI AgentKit vs Traditional Workflows: The Complete 2025 Comparison Guide

OpenAI AgentKit marks a new era in automation by making it possible to create and deploy AI agents without coding, through a simple visual interface. Composed of three modules — Agent Builder, ChatKit, and Evals — it accelerates the design, testing, and deployment of intelligent agents while making the digitalization of workflows more agile and accessible.

AI and No-Code: The New Alliance That Accelerates the Digitalization of the Supply Chain

The alliance between AI and no-code accelerates the digitalization of the Supply Chain. It makes it possible to automate workflows, optimize stocks and make innovation accessible to all businesses, without complex development. A winning duo for more agile, efficient and sustainable supply chains.

Generative AI: a new performance driver for the Supply Chain

Generative AI is revolutionizing the Supply Chain by combining creativity and operational performance. From planning to distribution, it optimizes decisions, anticipates risks and stimulates innovation to build smarter and more sustainable logistics.

AI in the Supply Chain: Key Applications, Benefits, and Prospects

AI is transforming the supply chain by improving forecasting, inventory, logistics, and supplier collaboration, with clear gains in costs, service quality and sustainability. Generative AI goes further by creating scenarios and action plans, accelerating design and operational resilience. Success is based on reliable data, solid governance, and progressive, results-oriented deployment.

Complete guide to measuring the ROI of customer support through AI in 2025

In 2025, the challenge of customer support through AI is no longer technological but methodological. Only a structured measure of ROI, integrating costs, revenues and satisfaction, can reveal its true strategic value.