AI for the industries that engineer and manufacture.

I help engineering and manufacturing companies adopt AI at the lowest possible cost, step into physics AI and physical AI, and source the machines and instruments that make it real.

Let's have a quick chat See how I can help
  • Farhad NazarpourPrincipal consultantPhysics AI & Physical AI
    AI Integration
  • PhD, Mechanical EngineeringSimulation, CFD and aerodynamics
  • Executive MBAStrategy, business cases and B2B sales
  • Automotive V&V leadershipValidation and verification in vehicle development
  • Published physics AI researchPhysics of Fluids 2025; award-winning paper at EuroBrake 2025

Three ways I work with engineering companies

Each can stand alone, and they often connect: a new AI use case may need better sensors, and a new production line is the right moment to plan for AI.

AI integration for engineering and manufacturing

Turn the data you already collect (test benches, sensors, simulation runs, quality records) into systems that save engineering hours and catch problems earlier, without an expensive transformation.

Typical work

  • Cost–benefit roadmap for AI adoption
  • Use-case assessment and prioritisation
  • Data readiness and pipelines
  • Predictive quality and maintenance
  • AI agents for engineering workflows
  • Validation and verification of AI systems

For

Engineering service providers, OEMs and suppliers, and manufacturing plants of any size.

Adopting today's AI at the lowest possible cost

Becoming an AI-ready company has a price, and it's more than software. I account for the full cost of transformation and weigh it against the savings AI will bring. Then we plan a path where early, low-cost wins pay for the next step, so AI starts saving money before it becomes a large investment.

Transformation costs I account for
  • Training and upskilling your people
  • Hardware and computing power
  • Software, licences and cloud services
  • Integration and process changes
Savings they are weighed against
  • Engineering hours saved
  • Fewer defects and less scrap
  • Less unplanned downtime
  • Shorter development cycles

Physics AI and physical AI

Replace hours of simulation with seconds of inference, and prepare your products and processes for AI that acts in the physical world.

Typical work

  • Surrogate models for CFD and FEA
  • Simulation-driven design optimisation
  • Physics-informed ML strategy
  • Physical AI and robotics readiness
  • Build, buy or partner decisions
  • Team training and upskilling

For

R&D departments, simulation teams, and companies taking their first steps into physics or physical AI.

Industrial equipment and components

The right machine or instrument, specified correctly and sourced from suppliers you can rely on.

What I supply

  • Industrial machinery
  • Measurement and test devices
  • Laboratory equipment
  • Components and spare parts for production lines
  • Technical specification and supplier comparison

For

Manufacturing units, test labs and production teams expanding or upgrading their equipment.

How a project runs

Small steps with clear decision points, so you never spend more than the evidence supports.

  1. Understand

    A short assessment of your processes, data, costs and goals. You get a written map of where AI or new equipment pays off, and where it doesn't.

  2. Prove

    A focused, low-cost pilot on your own data or production line, with success criteria agreed before any work starts.

  3. Scale

    Rollout, integration with your existing tools and suppliers, and a hand-over so your team can run it without me.

Portrait of Farhad Nazarpour

Engineer first, then AI

I'm Farhad Nazarpour. I trained as a mechanical engineer, spent years in CFD and aerodynamic simulation, and now lead validation and verification work in automotive development. That background shapes how I approach AI: it has to respect physics, survive validation, and pay for itself.

My research on physics AI includes TripOptimizer, a generative model for aerodynamic design that achieved up to 11.8% drag reduction, published in Physics of Fluids. I've also worked in B2B sales across the DACH region, so I know both sides of an equipment or technology decision.

  • PhD in Mechanical Engineering and Executive MBA
  • Outstanding Paper Award, EuroBrake 2025
  • Founder of a physics AI startup (NVIDIA Inception member)
  • Works in English, German and Persian

Insights

Short, practical notes on AI in engineering and manufacturing.

Let's have a quick chat

A short intro call is free. Tell me what you're building or buying, and I'll tell you honestly whether I can help.

Email
farhad@nazarpour.co
LinkedIn
linkedin.com/in/farhad-nazarpour
Based in
Munich, Germany. Working worldwide
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