The New Enabler of Quality.
A cutting edge, fully-integrated
AI-driven system consisting of
Bespoke hardware (Cameras & proximity sensors),
Proprietary Deep Learning Neural Networks and
Advanced analytics dashboards.
Defect-proofing Production through limitless capabilities of AI Integrated
Vision Inspection Systems -
Convergence of image acquisition hardware and
Deep Learning Neural Networks and image analytics.
Camera agnostic; wide
range of cameras available
depending on application
Choose between an
On-Premise or Cloud
Deployment of EaglAI
based on the user’s preference
dashboards to monitor
No Code Model Training
Our smart annotation,
model selection and training tool, EaglAI Train, enables user driven model development without
Can be easily integrated
with existing Line MES
or automation systems
through a 24 Volt output signal
Eliminate trade-offs in quality control in high speed environments with real-time, consistent quality control and complete accuracy even at 20+FPS (Frames Per Second)
Ease of Integration
Fully-configurable system works with up to 4 different cameras to detect minute anomalies
of various objects irrespective of position & orientation.
Variations in products are constantly added to reference/library without human intervention.
Complete visibility of automated processes, through a simple User Interface.
Accurate Fault Assessment
Deep Learning Neural Networks develop logical reasoning capabilities by self programming. Eliminates need for additional processes.
Complete reliability in fault detection, through consistency not possible in traditional systems. Amplifies confidence in product quality and life cycle.
Key Value Proposition
Creating True Value
Resin Impregnation Defect Detection
The Resin Impregnation process is used to get rid of the porosity and blow holes
(Caused by air bubbles) in Aluminium Die Cast parts.
The client receives cast metal parts from other companies.
• White and yellow rust on the metal
• Black residue
• Defects in the metal object itself, such as dents, caused by transport or handling
Currently parts are checked manually but this is not a 100% fool-proof process.
With EaglAI, we are able to create a master defect database and use
our proprietary algorithms based on Deep Learning and Artificial Neural
Networks to fully automate the inspection process