Top-grade Custom software development services

We deliver top-grade custom software development services specialized in CAE simulation. We build high-fidelity, high-performance bespoke simulation solutions tailored to unique enterprise workflows. By integrating deep domain expertise with advanced numerical methods, we empower clients to accelerate innovation and gain a competitive edge through fully customized tools—from core solvers to user interfaces.

How we create your Customized Codes

Our development follows a structured yet flexible process, ensuring your custom software not only meets but evolves with your specific business objectives and technical environment.

Discovery

We collaborate with your team to understand business needs, technical constraints, and user expectations.

Design & Architecture

We design the software architecture, select optimal algorithms, and plan the technical roadmap for scalable and robust development.

Core Development

Our experts implement the core numerical solvers, physics models, and data structures, focusing on accuracy, performance, and reliability.

Integration & Interface

We seamlessly integrate the new modules with your existing tools (CAD, CAE, etc.) and develop an intuitive user interface for your engineers.

Validation & Deployment

The solution undergoes rigorous testing against benchmarks and real-world scenarios, followed by smooth deployment and user training.

Support & Evolution

We provide ongoing technical support and work with you to continuously enhance the software, adapting to new challenges and opportunities.

Technical Stack & Capabilities

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Core Computation Layer

  • C++17/20 – Serving as the foundation for high-performance, memory-efficient numerical solvers and computational kernels, ensuring deterministic real-time performance for complex physics simulations.
  • Fortran – Specialized for inheriting, optimizing, and integrating legacy scientific computing codebases, preserving decades of validated algorithms while modernizing their interoperability.
  • CUDA – Enabling GPU-accelerated parallel computing for computationally intensive algorithms, delivering order-of-magnitude speedups for linear solvers and particle systems on NVIDIA hardware.
  • OpenCL – Providing cross-platform GPU acceleration capabilities, ensuring performance optimization across diverse hardware architectures including AMD and Intel platforms.
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Framework & Tool Layer

  • Eigen – Offering high-performance C++ template library for linear algebra, matrix operations, and numerical solvers with minimal memory overhead.
  • PETSc – Delivering scalable tools for solving large-scale scientific applications on parallel computers, supporting both structured and unstructured grid problems.
  • OpenMP – Enabling shared-memory parallel programming for multi-core processors, optimizing loop-level parallelism and task-based computations.
  • MPI – Facilitating distributed-memory parallel computing across high-performance computing clusters, supporting large-scale simulation scalability.
  • CMake – Streamlining cross-platform build system generation and dependency management, ensuring consistent software builds across Windows, Linux, and macOS environments.

Interface & Ecosystem Layer

  • Python API – Providing flexible scripting interfaces for rapid prototyping, automated pre/post-processing pipelines, and user-customizable workflow integration.
  • MATLAB/Simulink Interfaces – Enabling seamless integration with control systems design and simulation environments, supporting co-simulation and model exchange capabilities.
  • Docker Containerization – Ensuring reproducible development and deployment environments through container technology, simplifying dependency management and deployment across different systems.

Problems We Solve (Client Pain Points)

  • Commercial software cannot implement custom physics models or constitutive relationships.
  • Deep integration with proprietary hardware/experimental equipment is required.
  • Existing solvers lack sufficient performance or cannot be parallelized.
  • Need to transform legacy academic code/research models into industrial-grade software.
  • Highly customized pre/post-processing and workflow automation is necessary.