DesignIQ.

The decision problem

What should we choose, configure or design?

Design and selection decisions explode combinatorially: every option you add multiplies the number of viable configurations, and the best choice depends on constraints that interact. Choosing a portfolio, configuring a network, partitioning a workload, or designing an architecture are all searches over an intractable space of structured choices, exactly where classical heuristics start approximating rather than solving.

Capabilities

What DesignIQ does.

Representative NP-hard problem families

Recognized mathematics beneath the decision.

DesignIQ recognizes these families in your problem and compiles each to the formulation and solver that fits, classical, AI, quantum-inspired, quantum or hybrid.

Where it applies

Reused across industries.

Composition

Rarely used alone.

DesignIQ decides the structure; ResourceIQ then places resources into it, ScheduleIQ times the activities, and RouteIQ moves things through it. Design and allocation especially are often solved together.

Hardware-independent execution

The API stays stable when the hardware changes.

You call DesignIQ in terms of your decision such as objectives, constraints and data, not in terms of a solver or a quantum architecture. The problem is captured in GradientIR and compiled to whatever executes it best: classical mathematical optimization, CPUs, HPC, GPUs, AI-based optimization, quantum-inspired methods, quantum annealing, gate-based quantum processors, or hybrid classical-quantum systems. When the execution technology evolves, your application does not have to change. We don't claim a quantum computer is in the loop when it isn't.