Making Visual Quality Inspection
Software
xis.ai provides no code, an end-to-end platform for AI visual quality inspection. A robust Vision AI platform enabling companies to navigate the entire AI life cycle effortlessly. With our solution, businesses can swiftly develop and customize AI solutions independently, establishing a secure foundation that minimizes risks and optimizes costs while driving revenue growth. Includes AI assistive labeling and active learning algorithms for fast and efficient process.
How it Works
Step 1
Train AI
Train the AI based on the dataset you Provided. Our web app and software allow you to effortlessly import your data, commence the labeling process for your items.
Step 3
Deploy
Thats it! Your model is ready to be used in your application.
Capture & Label Images
Define your dataset and import it into either our web platform or the standalone desktop app.
Step 2
Test
Once the Labeling in process is completed you can export the model and use it in your application.
Step 4
Use Cases
Features
Train the AI based on the dataset you Provided.
AI-Assisted Labeling
Fast AI-assisted labeling streamlines the annotation process, harnessing the power of artificial intelligence to swiftly and accurately label images.
Plug & Play
Enables easy "Plug n Play" integration for a hassle-free setup. Effortless deployment with a user-friendly interface.
No Expertise Required
User-friendly design, no technical expertise needed. Intuitive interface for easy deployment of tailored solutions.
Edge Device Compatible
Utilizing edge computing, data is processed locally near its generation point, reducing latency, improving efficiency, and enhancing overall system performance.
Collaborative Platform
A robust system allowing multiple users to collaborate seamlessly on labeling and training computer vision models, enhancing productivity, accuracy, and workflow efficiency.
Fully Customizable
Customizable labeling and training processes ensure the software fits your needs, optimizing efficiency and accuracy for training computer vision models in quality inspection.