AI.SEE GmbH
About us
Manual visual inspection ties up staff, and the same defect type is rated differently depending on inspector and shift. Rule-based machine vision reaches its limits on varying surfaces.
AI.SEE™, the AI quality inspection of the elunic group, inspects parts with camera and AI, inline or in the lab: surfaces, weld seams, castings and porosity, coil and strip, metallographic micrographs. The model is trained on your inspectors' defect classes and ratings and then judges every part by the same standard.
AI is not plug-and-play. We show you up front, on your own images, whether your inspection task can be solved. Bring sample parts or images to our booth B3-622.
Have your images checked: https://www.elunic.com/aisee/kostenlose-erstanalyse/
Products & services
Surface & Coating Defect Analysis
Automated visual inspection for scratches, dents, coating defects, rust, cracks, waviness, and color deviations. Designed for production teams that need faster feedback, less rework, and better traceability. AI.SEE™ delivers high-speed detection for complex surface anomalies, helping manufacturers reduce manual inspection effort and prevent defective parts from moving further down the supply chain.
End-of-Line (EoL) Quality Control
Complete visual quality assurance at the final stage of your production line. AI.SEE™ acts as a reliable gatekeeper, adapting to existing infrastructure through flexible retrofit, stand-alone, or inline deployment paths to ensure 100% reliable defect detection before shipment.
Automated Micrograph Analysis with AI
The micrograph inspection is an important step in material analysis.This is because it is used to analyse the microstructure of material samples in detail. Micrograph analysis is often used in metallography, materials science and quality control to get to the bottom of the internal structure of materials. This method of material analysis is very time-consuming, as thin sections must first be taken from the metal samples, which are then etched and finally analysed under a microscope in order to examine phase fractions, inclusions, microstructures and other microscopic features. However, these parameters provide information about the quality of the material test. In order to automate this process, quality testing is increasingly being carried out using Metallography software with artificial intelligence.