Electronic parts catalog software, built from the content you already own
Most parts catalog software assumes you will bring it clean data. Metadome.ai starts from what OEMs actually have: engineering drawings, scanned service manuals, 2D part images and part numbers.
One model, every surface
A flat drawing, a scanned manual, a part number, a plain sentence: whatever you have becomes one 3D model. Everything your network needs after that is just a view of it: parts commerce, technician guidance, training, and your own apps through an API and embeddable viewer.
What you hand over
- 2D drawingthe PDF your OEM shipped in 1998
- Service manualscanned, static, out of date
- Part numberSAMPLE-0141 · REV A
- A sentence“180-seat narrow-body…”
Formats: PDF, DWG, STEP, PNG.
You don't operate it. You talk to it.
The same pipeline as a conversation. Upload anything. The agent reads it, asks the questions an engineer would, and builds the part live in front of you. Approve it, prove it, render it. No tools to learn.
Why the exploded view matters
A buyer who can rotate an assembly and click the part they can see does not guess a part number. That is the difference between a catalog that describes parts and one that identifies them.
Measured in the field, at OEM scale.
The names behind 400K+ parts brought to life.
- Daimler
- GM
- Lexus
- MG
- Jeep
- Audi
- Nissan
- Stellantis
- Maruti Suzuki
- Vinfast
- Tata Motors
- Mahindra
- Air India
Before you ask.
Software that links parts lists to diagrams so technicians, dealers and customers can identify and order the correct part.
No. There is no re-authoring and no CAD rebuild — the platform works from the drawings, manuals and part images you already own.
PDF, DWG, STEP and PNG.
An interactive 3D model that runs parts commerce and AI-guided technician workflows from the same source.
See it on your own drawings
Bring a drawing set or a service manual. We will show you the 3D model, the parts experience and the technician workflow built from it.
- 30%Parts Engagement
- 25%Faster Technician Enablement
- 40%Manual Effort Down
- 400KParts Delivered