Photograph the component
The technician photographs the required spare part on site using a smartphone.
Hauer · AI app for lift servicing
Identify and order spare parts by photo
lift lens connects AI image recognition with the Hauer Elevatorshop product catalogue and direct ordering.
The starting point
When every minute of service counts
Technicians must reliably identify lift and escalator components on site. Similar designs, missing labels and a large spare parts inventory can make searching difficult.
A wrong part causes extra coordination, returns and longer downtime. A mobile solution was needed to connect recognition and procurement seamlessly.
The workflow
From camera image to matching product
Identify with AI
The integrated AI analyses the image and matches the component to products in the Elevatorshop database.
Review matches
Matching, verified spare parts appear within seconds.
Order directly
The selected product can be ordered directly from the app.
Less search timeautomated identification
Fewer errorsmatching products without manual searching
Faster servicerecognition connected to ordering
Practical benefits
Designed for on-site work
The app is designed for lift service technicians and engineers. It is mobile, tailored to their workflow and available in German and English.
- AI-powered spare part recognition
- Matching against Elevatorshop inventory
- Direct ordering workflow
- Available for Apple iOS and Android
- For lifts and escalators
External project source: The functionality and benefits are also described in the article by Hauer – the elevatorshop .
Relevant expertise
What this project brings together
Computer vision
Visual features match real components with the right product data.
Mobile application
The feature is available where the problem arises: directly during servicing.
Process integration
Recognition leads directly into the operational ordering process.
Your use case
Could AI reliably recognise your products too?
We examine the data, process and integration needs together.
Discuss your project ↗