One of our clients managed a supply chain spanning 47 suppliers, 12 warehouses, and tens of thousands of SKUs. Planning and reporting were entirely manual — a weekly Excel export followed by hours spent reconciling data.
Our task: automate, accelerate, give managers real-time data access. We chose Java 21 + Spring Boot 3.2 as the backend — a proven stack for enterprise-grade systems.
The system grew to over 300 REST endpoints. Each module — procurement, warehousing, delivery, forecasting — had its own API. Integration with the client’s ERP required handling six different data formats.
The key innovation was the Text2SQL module. Managers could type questions in natural language: “How many units of product X were ordered from supplier Y last quarter?” — the system translated this into SQL and returned the answer in seconds. We built it on a language model fine-tuned on the client’s database schema.
The second AI component is RAG (Retrieval-Augmented Generation) for documentation. The system had access to hundreds of supplier contracts, product specifications, and internal procedures. Staff could ask questions about specific contract terms — e.g. “What is the warranty period for refrigerated products from supplier Z?” — and receive precise answers with the exact source document quoted.
Results after 6 months: weekly report preparation time dropped from 8 hours to 20 minutes. Order error rate fell by 34%. Managers have real-time dashboard access instead of a weekly snapshot.
Want to learn more about how we build enterprise systems with AI? Reach out: [email protected]