Case study / Manufacturing
Manufacturing: many customer orders, one coordinated allocation.
Connecting inventory, recordings, and historical results to a custom order-allocation algorithm that groups customer orders into a single consolidated order.
Our manufacturing work connected the company’s inventory system, recordings, and historical results to a custom order-allocation workflow. The aim: group compatible customer orders into one consolidated order, reducing waste and improving operating efficiency.
Bring the operating context together
Inventory records describe what is available. Recordings capture working context. Historical results show what happened before. We connected these inputs so the allocation workflow could use them together.
Use the right method for each part
The system combines a knowledge graph, retrieval-augmented generation (RAG), a classifier, tool calls, and our execution harness. The graph links related information; retrieval brings relevant evidence into the task; classification helps organize the inputs.
We developed and optimized a custom algorithm for the allocation problem. The harness coordinates the data access, ordering steps, and tool use needed around that computation.
Turn separate orders into a coordinated order
The allocation workflow groups customer orders so they can be carried into one exact consolidated order. This gives the business a way to coordinate demand and reduce the waste created by handling orders in isolation.
Judge it by the operating result
The business objective is lower waste and better efficiency. Useful measures include material waste, allocation quality, manual coordination, and the time required to produce an actionable order. The custom algorithm is one part of delivering that operating result.