Vertex Optimization offers a decision‑support platform that converts process data from chemical and metal plants into linear, mixed‑integer and nonlinear optimization models using the Gurobi solver. The system generates optimal production schedules, inventory policies, and logistics plans, and provides scenario analysis and real‑time recommendations through web dashboards or API integration with ERP/MES systems. It also incorporates machine‑learning forecasts and equipment performance insights to improve utilization and reduce energy and environmental impact.
Funding
Funding not disclosed
Founders
Product
Problem
Process manufacturers and metal producers often rely on manual spreadsheet models for flowsheet design, raw material procurement, supply‑chain planning, and batch scheduling. These ad‑hoc tools are error‑prone, difficult to scale, and hide hidden economic losses and capacity bottlene bottlenecks. Consequently, companies struggle to quantify benefits, improve utilization, and respond quickly to changing market conditions.
Solution
Vertex Optimization delivers a decision‑support platform that transforms raw process data into mathematically rigorous optimization models. Using linear, mixed‑integer and nonlinear programming—leveraging the Gurobi solver—the system generates optimal production schedules, inventory policies, and logistics plans for chemical and metals operations. The platform couples advanced analytics and data‑science techniques (machine learning, clustering, reinforcement learning) to enrich models with demand forecasts and equipment performance insights. Its modular architecture separates data ingestion, model definition, and user interface, enabling seamless integration with existing ERP, MES, or custom databases. Users can run “what‑if” scenario analyses, visualize resource utilization, and receive actionable recommendations through web dashboards or API endpoints. An agile development approach ensures rapid delivery of tailored solutions that capture the detailed constraints of each plant while reducing planning effort and minimizing energy and environmental impact.
Target Audience
Primary customers are planning engineers, supply‑chain managers, and production schedulers at chemical and metals companies, as well as engineering consultancies that require custom, high‑performance optimization solutions for complex process operations.
Features
- Modular toolchain separating data storage, mathematical models, and UI for flexible integration with legacy systems
- Pre‑built optimization modules for flowsheet design, raw‑material purchasing, supply‑chain planning, inventory optimization, batch scheduling, mixing/blending, and capacity planning (chemical)
- Specialized logistics and port optimization modules for metals industry operations
- Advanced analytics suite offering data visualization, pattern detection, and demand forecasting to feed optimization models
- Mathematical programming engine supporting linear, mixed‑integer, and nonlinear formulations via Gurobi Optimization
- Data‑science layer with machine‑learning models, clustering, reinforcement learning, decision trees, and regressions for data‑driven decision support
- Scenario management and “what‑if” analysis tools with instant recalculation of optimal plans
- Secure web dashboard and RESTful API for real‑time results delivery, reporting, and integration with ERP/MES platforms
- Agile, iterative development process delivering incremental value and rapid customization