Insider letter
- Mind Success has launched two software platforms designed to accelerate quantum hardware development through AI-driven materials discovery and predictive hardware modeling.
- The company’s Quantum Materials Discovery Platform reviews more than 150,000 candidate materials and automatically generates density functional theory simulations to evaluate promising options.
- Its digital twin framework models ambient noise around qubits and generates predictive control signals designed to reduce decoherence across multiple quantum computer architectures.
PRESS RELEASE – Mind Success, a startup focused on predictive modeling for quantum technologies, has launched two software platforms designed to accelerate the development of quantum hardware by helping researchers identify new materials and reduce ambient noise that affects the performance of qubits.
The company, based in Saudi Arabia and the United States, said the offerings include an AI-based Quantum Materials Discovery Platform and Digital Twin Framework designed to model and optimize quantum hardware environments before building or testing physical devices.
The Materials Discovery Platform uses artificial intelligence to explore more than 150,000 possible quantum materials and automatically generate density functional theory (DFT) simulations to evaluate the most promising options. According to the company, the platform is intended to reduce the time required to identify suitable materials for applications such as quantum processors, sensors and cryogenic components.
According to Mind Success, the software acts as a searchable database that combines large-scale materials testing with automated first-principles verification, reducing the need for early-stage laboratory experiments.
The company’s second product, the Digital Twin Framework, is designed for integration into existing quantum hardware systems. The software creates a predictive model of the qubits’ environment, enabling the prediction of decoherence sources – environmental disturbances that cause qubits to lose their quantum state – and the generation of feedforward control signals designed to compensate for these effects.
According to Mind Success, the framework can model more than 1,000 ambient sound modes simultaneously and generate control signals in about 25 picoseconds. The company said the software is compatible with multiple quantum computing architectures, including superconducting qubits, semiconductor quantum dots, trapped ions and diamond-nitrogen vacancy centers.
Mind Success also said its simulation framework scales linearly with system size and does not have the exponential computational growth associated with many traditional quantum system simulations. The company said this enables larger and more detailed environmental models while reducing computational burden.
Together, the two products are intended to cover different phases of quantum hardware development. The materials platform focuses on identifying suitable materials before fabrication, while the digital twin software is designed to optimize the operating environment of quantum devices after material selection.
The company said the combined approach aims to reduce the lengthy trial-and-error process often associated with developing quantum hardware, where identifying suitable materials and mitigating ambient noise can require years of experimental work.
According to Mind Success, both software platforms are available as platform-independent tools for quantum hardware developers working with multiple qubit technologies.
https://thequantuminsider.com/2026/07/16/mind-success-unveils-quantum-materials-discovery-platform-digital-twin-software-for-hardware-development/
