SOPtimAi is an AI-powered Integrated Business Planning platform that unifies production optimization, inventory planning, logistics, and customer supply and source mapping. It integrates planning decisions to maximize profit, beyond closing the demand-supply gap.
Volume balancing can overlook asset utilization, internal material movement, logistics dependencies, customer prioritization and financial outcomes. These gaps can lead to costly, suboptimal decisions.
SOPtimAi brings operational constraints, financial variables, production capabilities, logistics limits, market demand and pricing signals into a unified optimization engine.<br>The platform evaluates 45,000+ decision variables, 60,000+ constraints and 10,000+ nonlinear constraints simultaneously.<br>Deploy on premises or in the cloud. Flexible, tailored connections can work with SAP, Oracle, custom ERP/M environments and spreadsheet-based inputs.<br>
Demand, price, plant data, inventory
Capacity, routing, logistics, business rules
Production, sourcing, allocation, stock
Implementable, profit-optimized plan
SOPtimAi replaces iterative planning what-ifs with one model that optimizes production, inventory and product demand-supply decisions together.
300 MMUSD+Opportunity estimate from the supplied brief
45,000+Optimized simultaneously
60,000+Including 10,000+ nonlinear constraints
Multi-SiteAcross products and plants
20 minAfter required inputs are provided
Profit-CentricInventory, availability and supply together
Profit-first optimization across the enterprise, beyond volume balancing.
Cross-functional IBP connects finance, production, inventory management and supply chain.
Inventory and product availability optimized as one connected problem.
45,000+ decisions considered together across production, inventory, internal logistics and customer supply.
Optimization run within 20 minutes of input provision, compared with days of iteration in legacy planning.
Purpose-built for multi-site, multi-product, multi-constraint industrial operations.
Choose a role to see how SOPtimAi supports its planning priorities.
Optimize 45,000+ decision variables across the corporation and identify potential untapped margin through AI-driven profitability optimization.
Roll out a stronger plan for inventory handling, sourcing and site-to-customer mapping.
Bring production, inventory and internal logistics into a profit-optimized S&OP cycle, with an optimization run within 20 minutes of receiving the required inputs.
Deploy on premises or in the cloud with tailored integration to SAP, Oracle, custom ERP/M environments and spreadsheet-based data.
Receive an optimized production and inventory management plan designed for implementation within physical operating constraints.
Planning models account for the operating constraints and commercial decisions of each industry.
Complex value chains, multi-site production interdependencies, inventory and allocation under volatile input costs.
Demand-driven S&OP and inventory planning across fast-moving, multi-SKU networks.
Constraint-heavy inventory and availability planning at plant and portfolio level.
Demand- and pricing-aware S&OP and inventory planning with margin in view.
SOPtimAi draws on Ingenero's S&OP and ERPM expertise, applied AI heritage and experience in industrial operations. Its planning approach is grounded in engineering and operational constraints.
Yes. Ingenero can help reduce both energy costs and emissions by optimizing energy-intensive systems such as furnaces, steam networks, and boilers. Our solutions reduce fuel and utility consumption, which directly lowers operating costs while also cutting associated greenhouse gas (GHG) emissions from energy use.
Sustainability consulting improves industrial operations as it helps in pinpointing inefficiency across every section, including water, energy, and process systems. In this way, organizations can take proactive measures and move towards net-zero goals.
Energy efficiency studies typically cover major utility and process systems such as boilers, furnaces, steam and cooling systems, compressors, pumps, refrigeration units, HVAC systems, and electrical distribution networks. These studies also extend to process-level energy use, helping to identify inefficiencies across the entire plant rather than at individual equipment alone.
Ingenero is known for combining engineering expertise with digital solutions such as AI, digital twins, and advanced analytics to deliver practical, implementable improvements in real-world plant operations.
