 # How AI Agents Save Millions: A Breakdown of Cases from EVRAZ and a Logistics Company Industry and logistics are two areas where the cost of a mistake is measured not in rubles, but in millions. An overheated furnace at a metallurgical plant wastes gas. A lost order in logistics means a broken contract. Manual management here operates at the limit of human capabilities. But there is a solution, and it has already been implemented. ## Case 1: EVRAZ — A Neural Network That Saves Gas At EVRAZ NTMK's hot rolling mills, billets are heated in furnaces to a temperature that allows the desired profile to be achieved. The process is energy-intensive — gas costs money, and overconsumption hits the cost price. The plant's engineers trained a neural network on historical data of furnace operating modes. The model analyzes current parameters: steel grade, billet thickness, rolling speed — and suggests the optimal temperature regime in real time. Result: reduced gas consumption per ton of rolled product. Exact figures are not disclosed, but on the scale of the plant, the savings amount to tens of millions of rubles per year. And this is without replacing equipment, solely through the algorithm. ## Case 2: A Neurobot for Logistics A logistics company faced a classic problem: orders (auctions, tenders, cargo) come from different sources. Some in 1C, some in Bitrix, some in SQL databases, some in Excel and a "ledger book." Dispatchers spend hours searching and cross-referencing. The developer integrated a local neurobot directly into the order search panel. The bot understands natural language: "find all tenders for metal transportation for March" — and provides a selection from all systems at once. No data migration, no years-long integrations. Result: order search time reduced from 15–20 minutes to 30 seconds. Manual entry errors are eliminated. ## What Do These Cases Have in Common? In both cases, AI does not replace people but becomes an interface to the data that already exists. It does not require restructuring the IT infrastructure. It simply analyzes what is already working and finds optimization points. ## How to Achieve the Same with ASI Biont The ASI Biont platform delivers the same effect without a team of data scientists. You connect your data sources — CRM, ERP, Excel, SQL, email — and the AI agent analyzes document arrays in 14 seconds, finds anomalies, builds reports, and offers solutions. For metallurgists: control of resource overconsumption. For logistics: a unified search panel. For retail: demand forecasting. For finance: payment auditing. 1500 tokens to start — try it on your data. Scalpel precision, lightning speed. [https://asibiont.com/](https://asibiont.com/)