Tensor CFD
Custom In-House CFD Solutions Powered by OpenFOAM


Break Free from Licensing Limits. Own Your CFD Workflow.

Since 2013, Tensor CFD has helped engineering teams bypass the high costs and rigid constraints of traditional, black-box legacy software. We develop fully customized, production-ready, in-house CFD applications using OpenFOAM as our core backbone.

Get absolute source code access, zero recurring seat licenses, and a simulation engine tailored precisely to your physical models and hardware architecture.


Why Choose Open-Source Solutions?

Traditional commercial CFD tools restrict your engineering potential with capped user licenses and limited User Defined Functions (UDFs). Tensor CFD unlocks your full capabilities.


Core Development Expertise

Leveraging over 13 years of specialized expertise, we manage the entire software development lifecycle to deliver fully integrated, production-ready CFD ecosystems.

  • Solvers & Numerical Algorithms: Development of custom, high-fidelity solvers for multi-phase flows, specialized heat transfer, and complex chemical reactions.
  • Automated Volume Meshing: Algorithmic, hands-free grid generation pipelines optimized for highly complex or shifting geometries.
  • Physical Model Integration: Implementation of advanced turbulence closures, non-Newtonian fluid behaviors, and custom porous media zones.
  • Coupling & Third-Party Tools: Seamless data exchange and coupling between OpenFOAM and external FEA, optimization, or CAD frameworks.
  • Specialized Post-Processing: Automated data extraction, custom visualization pipelines, and targeted report generation tools.

Our Comprehensive Development Lifecycle

We don’t just hand over raw code. We deliver robust, enterprise-grade software backed by continuous care and maintenance.

[Requirement Scoping] ➔ [Custom Code Implementation] ➔ [Rigorous Validation] ➔ [Deployment & Support]

Meet Our Product Development Experts

Our multi-disciplinary team ensures that your custom CFD environment is scalable, user-friendly, and mathematically robust.