Supply Chain Chatbots

Supply Chain Chatbots are AI agents that integrate with corporate ERP systems to provide natural language information on orders, shipments, warehouses, and supply chain data. Via API they access management system data in real time and respond to operators and customers on every digital channel, 24 hours a day. Unlike traditional rule-based chatbots, they use large language models (LLM) and the RAG system to understand freely worded requests — "where is order 89234?", "how many units are left in stock?" — and return precise answers based exclusively on company data. The result is immediate access to operational information without having to navigate the ERP: fewer interruptions for the IT and customer care teams, response times that drop from hours to seconds, and customers who check the status of their shipments autonomously.

Crafter.ai integrates via API with any ERP system: SAP, Oracle, Microsoft Dynamics, Infor, Epicor and custom management systems. The No-Code Conversation Designer allows you to configure conversation flows without advanced technical skills, connecting the chatbot to ERP APIs to retrieve real-time data on orders, stock and shipments. A typical integration follows three steps: the ERP (or WMS/TMS) APIs are mapped to the agent's conversational actions, the response perimeter is defined by loading catalogs, price lists and manuals into the knowledge base through the RAG system, and the agent is published on the chosen channels — web chat, WhatsApp, email or internal applications. No changes to the existing ERP system are required: the chatbot operates as a conversational layer on top of the infrastructure already in use, and the team can update flows and content autonomously.

A logistics ERP chatbot can automate shipment tracking, order status verification, warehouse management (product location, available quantities, reorder thresholds), delay or anomaly notifications, KPI report generation, staff onboarding and customer care requests related to orders. In practice it covers the high-volume repetitive processes where operators and customer service lose the most time: answering "where is my order?", checking stock levels, updating a customer on a delivery. Higher-value activities — exception handling, negotiations with carriers, procurement decisions — remain with people, who however work with data already collected and organized by the AI agent. According to McKinsey, embedding AI in operations reduces logistics costs by up to 20% and inventory levels by up to 30%.

Crafter.ai can be activated quickly thanks to its no-code platform and pre-configured APIs. An informational chatbot — operational FAQs, service information, first-level customer support — is typically online in a few days. Full integration with the ERP system and the supply chain takes from two to a few weeks, depending on the complexity of the APIs to connect and the processes to automate. The recommended approach is incremental: start with a high-volume use case, for example shipment tracking, measure the result with the conversational analytics dashboard, and progressively extend the agent to other processes such as orders, warehouse and reporting. This way the value of the investment can be verified within the first weeks of use, without waiting for the entire project to be completed.