Joinery · InteriorsCase 01
Ehm & Eitel
From hand sketch to photorealistic rendering in minutes. 70% time saved in quote visualization.
AI-native design & engineering studio · Munich
Bringing AI to where physical products are made.
Product design, configurators and AI applications — from vehicles to furniture. We build solutions that work and teams that master them. On-premise on request.
Impact in numbers
14 yearsAutomotive · BMW · Byton · NIO
–60%Quoting time through workflow automation
–45%Prototyping time with GenAI pipelines
+40%Conversion through faster visualization
On-premiseFull data sovereignty
Services
Three fields, one principle: built, not advised.
Field 1
Product design & engineering
- For
- Manufacturers who want to move from brief to decision-ready design faster.
- What
- Concept & exterior design, package, product definition, 3D modelling, photorealistic renderings — AI-accelerated, with automotive process discipline.
- Outcome
- Decision-ready design states in weeks instead of months.
Field 2
Configurators & AI applications
- For
- Manufacturers with configurable or explanation-heavy products.
- What
- 3D configurators, sketch-to-rendering, custom-built micro-applications. MVP in 4–6 weeks, fixed price, then care package.
- Outcome
- Customers see their product before it is built.
Field 3
AI enablement & agentic setups
- For
- Teams and companies that want to use AI productively instead of just talking about it.
- What
- From proven AI tools to agentic work environments — plus coaching that truly brings your team along: onboarding, new ways of working, the right mindset.
- Outcome
- Your team works measurably faster within weeks — with tools and a mindset that stay.
Process
Three steps, no slide war.
01
Analyze
We understand product, process, bottleneck — compact, no slide battle.
02
Build
Design, application or setup — fixed price, clear milestones, visible progress weekly.
03
Deploy & Evolve
Delivery into your environment, team onboarding, ongoing development via the care package.
Before / After
The same process. Once without, once with AI.
Without AI
Quoting timeCalculated by hand
Prototyping timeClassic 3D pipeline
Sales conversionCatalog & PDF
With Request Change
Quoting timeWorkflow-automated−60 %
Prototyping timeGenAI pipeline−45 %
Sales conversionReal-time visualization+40 %
Drag to compare
Cases
Selected references.
Academic partnershipCase 02
Hof University · “AI Design Lab”
GenAI tools for 15 workstations — on-premise on their own GPU cluster, including training.
Automotive · EVCase 03
Vehicle program, Asian manufacturer
Full product definition for an electric off-road vehicle — to design approval in 8 weeks.
Industrial automation · EnablementCase 04
Festo
AI enablement for development teams: hands-on workshops, agentic work environments, onboarding included.
Why Request Change
Why work with us.
01
Engineer, designer, AI developer — without interface loss.
Whoever designs also builds. No translation loss between creation and code.
02
Automotive discipline.
14 years at BMW, Byton, NIO: quality gates, clean documentation, fixed-price reliability.
03
Hands-on, not slides.
You get running systems, trained teams and documented handovers.
04
We work AI-native ourselves.
Our studio runs on the same workflows we build for you — you buy lived practice.
05
Data sovereignty.
On-premise deployment, your own GPU infrastructure possible — your data stays in-house.
06
Tools and people together.
AI rarely fails on the technology — it fails on mindset. That is why onboarding and coaching are part of every project.
About Marcus
Marcus Görner
Founder · Request Change · Hechendorf near Munich
14 years in automotive: BMW, Byton, NIO. Teaching role at Hof University (“AI Design Lab”). Building Request Change as an AI-native studio: a small tip of the spear, senior quality.
FAQ
The questions from the intro call.
What does a project with Request Change cost?
Fixed price instead of day-rate surprises: after the intro call you receive a fixed-price offer with clear milestones. A configurator MVP takes 4–6 weeks, followed by support via the care package.
How quickly do we see results?
Decision-ready design states in weeks instead of months, an MVP in 4–6 weeks — with visible progress every week. Teams work measurably faster after the enablement.
Does our data stay in-house?
Yes, fully on request: on-premise deployment on your own GPU infrastructure — as for the “AI Design Lab” at Hof University; sensitive data stays in-house at the highest data-security level.
Does our team need prior AI knowledge?
No. Onboarding and coaching are part of every project — tools, new ways of working and the right mindset. AI rarely fails on the technology; it fails on mindset.
What makes Request Change different from an AI consultancy?
Built, not advised: you get running systems instead of slides. Whoever designs also builds — design, engineering and AI development without interface loss, backed by 14 years of automotive process discipline.
How do we get started?
A 30-minute intro call — concrete, no obligation. You describe the bottleneck, we tell you honestly whether and how AI helps. Then a compact analysis, no slide war.
Contact
Let’s talk about your product.
30 minutes, concrete, no obligation — you describe the bottleneck, we tell you honestly whether and how AI helps.