Nexma MathEngine
Provably Optimal Spatial Decisions
Turn spatial constraints into optimal, auditable plans. MIP, vehicle routing, constraint programming, and simulation solvers replace guesswork with mathematics that proves it found the best answer.
How Optimization Works
Formulate. Solve. Prove It's Optimal.
Nexma MathEngine turns your goal and the world model's constraints into a formal optimization problem, dispatches it to the right solver, and returns a plan that's provably optimal — with the optimality gap to prove it.
Objective
minimize Σ cost · x
Subject to
Optimality gap
12.4%
✓ Proven optimal
Legacy Challenges
Why Manual Planning Leaves Value Behind
Spatial plans built by hand or by rule-of-thumb satisfy a deadline, not an objective. They ignore constraints, leave cost on the table, and can never prove the answer was the best one available.
Guesswork Plans
Rules of thumb and manual layouts produce a workable answer, not the best one — quietly leaving real cost and capacity on the table.
Core Capabilities
Mathematical Optimization, Built In
Nexma MathEngine brings a full family of solvers to the world model, so spatial problems are formulated, solved, and explained automatically.
Optimal under hard constraints
Mixed-integer programming finds the lowest-cost design that satisfies every constraint — siting, capacity, budget — and proves its optimality.
Product Benefits
Replace Guesswork with Provable Optimality
Cut cost, respect every constraint, and hand stakeholders a plan that proves it's the best one — not just a plausible one.
Cut cost with provable optimality
Optimization routinely finds designs and routes that beat hand-built plans on cost and capacity — and shows exactly how much was saved.
Respect every constraint, automatically
Engineering rules, budgets, and regulations are encoded as constraints the solver must satisfy, so plans are valid before anyone reviews them.
Defend every decision
Each result comes with the objective, the constraints, and the optimality gap — an auditable record stakeholders and regulators can trust.
Feature Details
A Solver Suite for the Physical World
Nexma MathEngine pairs a family of optimization solvers with automatic formulation and explainability, all wired to the world model.
MIP & Linear
Mixed-integer and linear programming for siting, capacity, and allocation problems with provable optimality.
Routing & Scheduling
VRP and constraint-programming solvers for fleets, crews, and tightly constrained schedules.
Simulation
Agent-based and discrete-event simulation to predict outcomes before committing resources.
Related Products
Explore the Spatial AI OS
One platform for all spatial data and workloads, from design to field operations.
FAQ
Get the Facts About Nexma MathEngine
Read the DocsIt is the optimization engine inside Nexma. It turns spatial problems — siting, design, routing, scheduling — into formal models and solves them with MIP, VRP, constraint programming, and simulation, returning plans that are provably optimal and fully auditable.
Network design and siting (MIP), fleet and crew routing (VRP), tightly constrained scheduling and assignment (constraint programming), and outcome prediction (simulation) — across any domain the ontology describes.
Manual plans satisfy a deadline; optimization satisfies an objective. The engine balances every constraint at once, routinely beats hand-built plans on cost, and proves how close the result is to optimal.
No. The agent formulates the problem from your goal and the world model, drawing constraints from the ontology automatically. You state the objective; the engine builds and solves the model.
Hybrid by design — small problems solve directly in the browser for instant feedback, while larger ones dispatch to a dedicated solver server. The engine routes each problem to the right place automatically.