List of Altair CFD Customers
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Since 2010, our global team of researchers has been studying Altair CFD customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Altair CFD for Computational Fluid Dynamics (CFD) from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Altair CFD for Computational Fluid Dynamics (CFD) include: SharkNinja, a United States based Consumer Packaged Goods organisation with 3688 employees and revenues of $5.53 billion, Prodrive, a United Kingdom based Professional Services organisation with 28 employees and revenues of $16.1 million, HL Mando Softtech India, a India based Automotive organisation with 300 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using Altair CFD, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Altair CFD customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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HL Mando Softtech India | Automotive | 300 | $10M | India | Altair Engineering | Altair CFD | Computational Fluid Dynamics (CFD) | 2008 | n/a |
In 2008, HL Mando Softtech India implemented Altair CFD alongside Altair HyperWorks and AcuSolve at its R&D centre in India. The deployment focused on CAE for automotive R&D, targeting thermal simulation of ECU casing and broader computational engineering workflows, with Altair CFD serving as the primary solver for fluid and thermal analysis.
Implementation emphasized improvements in meshing and solver throughput, configuring meshing automation, thermal analysis pipelines and structural analysis workflows to support iterative design validation. The work leveraged Altair HyperWorks for pre-processing and AcuSolve as part of the solver stack to standardize mesh quality and runtime consistency across simulations. Operational coverage included simulation engineering and product development teams within the automotive R&D site, with CAE workflows formalized to manage models and simulation artefacts. The project produced faster, higher quality simulation results and delivered up to 30 to 40% reductions in product development time, shortening time to market.
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Prodrive | Professional Services | 28 | $16M | United Kingdom | Altair Engineering | Altair CFD | Computational Fluid Dynamics (CFD) | 2008 | n/a |
In 2008, Prodrive implemented Altair CFD to bring computational fluid dynamics capability in-house for detailed analysis of race car engine water jackets in its automotive R&D operations in the United Kingdom. The deployment centralized solver execution and post-processing within engineering, enabling direct control of simulation cadence and experiment iteration.
The implementation centered on Altair AcuSolve as the production CFD solver, with AcuFieldView used for streamlined post-processing and visualization. Prodrive configured automated, repeatable CFD workflows including meshing setup, solver parameterization, batch run orchestration, and standardized result extraction to reduce manual intervention.
Operational coverage focused on R&D engineering for engine thermal management and fluid pathways, moving simulation activities into internal engineering labs and reducing reliance on external simulation vendors and separate lab testing. The project produced repeatable simulation templates and standardized reporting feeds for engineering review workflows.
Governance emphasized workflow standardization and automation, with documented process templates for CFD case setup, convergence checks, and post-processing review to accelerate engineering decision-making. Altair CFD served as the central application for solver and post-processing orchestration, Apps Category .
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SharkNinja | Consumer Packaged Goods | 3688 | $5.5B | United States | Altair Engineering | Altair CFD | Computational Fluid Dynamics (CFD) | 2015 | n/a |
In 2015, SharkNinja implemented Altair CFD as a Computational Fluid Dynamics capability within its consumer goods R&D organization in the United States. The deployment leveraged Altair HyperWorks solvers including AcuSolve to embed simulation-driven design into appliance development workflows, aligning SharkNinja Altair CFD Computational Fluid Dynamics R&D to engineering practice.
The implementation focused on fluid flow and thermal simulation use cases, applying AcuSolve and related solver toolchains to analyze vacuum and fan aerodynamics and mixer flow behavior. Altair CFD was used to iterate virtual prototypes, exercise parametric design variants, and validate performance targets prior to physical builds, reducing dependence on physical test cycles.
Operational scope covered product engineering and testing functions in SharkNinja consumer goods R&D, with simulation outputs feeding design reviews and test planning. The engagement emphasized workflow change from physical-first validation to simulation-first evaluation, enabling engineers to identify durability and quality risks earlier in the design cycle.
Governance and process change centered on instituting simulation-driven design practices and integrating solver results into product decision gates. The program explicitly reduced the number of physical tests, saved engineering time, and improved product durability and quality as reported by the R&D organization.
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