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VeloxQ

VeloxQ provides enterprises with a physics‑inspired hybrid solver that tackles large‑scale Quadratic Unconstrained Binary Optimization (QUBO) problems on conventional CPUs and GPUs.

Warszawa, Masovian VoivodeshipFounded 202214300+ followers
Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Enterprises often face combinatorial optimization challenges—such as scheduling, logistics, portfolio allocation, and drug discovery—that involve millions of binary variables and dense, fully‑connected interaction graphs. Traditional solvers either cannot scale to these sizes or require specialized quantum hardware that is not yet widely available, leading to long runtimes and suboptimal decisions.

Solution

VeloxQ offers a physics‑inspired hybrid solver platform that tackles large‑scale Quadratic Unconstrained Binary Optimization (QUBO) problems on conventional compute infrastructure. By combining advanced classical heuristics with quantum‑inspired algorithms, the system delivers high‑quality solutions quickly, even for instances with tens of millions of variables and dense connectivity. The platform is hardware‑agnostic, allowing seamless integration with any quantum hardware provider to enable future hybrid quantum‑classical workflows. Users can run optimization workloads today while remaining prepared for emerging quantum acceleration, reducing time‑to‑insight across sectors such as scheduling, logistics, finance, and drug discovery.

Target Audience

Primary customers are enterprise optimization teams in industries such as manufacturing, supply chain, finance, and pharmaceuticals that need to solve large, complex QUBO problems at scale.

Features

  • Physics‑inspired algorithms that model QUBO problems using principles from statistical mechanics for efficient search of solution space
  • Hybrid execution engine that blends classical advanced heuristics with quantum‑inspired techniques to improve solution quality and speed
  • Capability to handle tens of millions of binary variables and fully‑connected dense graphs without requiring graph embedding
  • Hardware‑agnostic design with APIs for integration to any quantum processor, enabling smooth transition to hybrid quantum‑classical pipelines
  • Scalable software architecture optimized for conventional CPUs/GPUs, allowing immediate deployment on existing enterprise compute resources
  • Domain‑specific solution templates for scheduling, logistics, portfolio optimization, and drug discovery to accelerate implementation
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