OptiMind

OptiMind is a small language model that converts natural-language descriptions of business problems into the mathematical formulations consumed by optimization solvers. It produces variable definitions, constraints, and objective functions for problems such as supply-chain design, workforce scheduling, logistics routing, and portfolio optimization. Training combines expert-aligned data with domain-specific hints, and inference includes self-checks that validate generated formulations before submission to a solver.

OptiMind targets the real bottleneck in operations research: not solver performance, which is mature, but the expert labor required to translate fuzzy business problems into solver-ready mathematics. By mapping plain language directly to formulations, the model puts advanced optimization within reach of teams that lack a dedicated OR engineer and shortens the iteration loop between requirement and result. Self-checking at inference time catches the most common formulation errors, increasing the rate of solver-ready outputs and reducing the cost of experimenting with mathematical models in routine business workflows.