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Robovision - AI-Powered Computer Vision Platform for Automation
Robovision specializes in providing an AI-powered computer vision platform that facilitates intelligent automation across multiple industries. Designed to operate seamlessly with existing hardware inventories, Robovision's platform processes visual input using advanced deep learning algorithms, delivering meaningful analysis that drives machine action. It's a versatile solution ideal for sectors like agriculture, healthcare, manufacturing, and more, enabling improved production yields, customized operations, and efficient resource management. The platform promotes ease of integration for users lacking extensive AI skills, simplifying the management of the AI lifecycle. Continuous innovation is ensured through regular updates, providing users with access to the latest advancements in vision intelligence, which in turn contributes to reduced resource demands and faster deployment times. Consequently, businesses can achieve a competitive edge and operational excellence by leveraging this advanced technology.
AI-powered Computer Vision
Robovision’s AI-powered computer vision platform enables intelligent automation. The platform gathers visual input, applies deep learning algorithms, analyzes results, and instructs machines accordingly.
Machine builders gain new potential with their current inventory, while production lines benefit from increased yield, enhanced customization, and minimized waste.
Focus on Your Core Business
The Robovision platform eliminates the need for extensive AI expertise, allowing users to extract the benefits of AI without coding skills. Data scientists can concentrate on innovation, so businesses can focus on key objectives without being overwhelmed by AI complexities.
Cost-effective
No need for a custom computer vision AI solution. The Robovision platform streamlines development, simplifies AI lifecycle management, and enables domain experts to handle complex tasks. You’ll see results faster.
Continuous Innovation
With a quarterly release cycle, the Robovision AI Platform continuously updates with the latest advancements in vision intelligence. Ensures reliable access to cutting-edge AI capabilities.
Faster Time-to-Market
With instant access to advanced vision AI capabilities, deployment time and resource demands are significantly reduced. It allows for greater flexibility and adaptability, helping you gain a competitive edge.
What Makes the Robovision AI Platform Essential?
AI platforms provide clear benefits over custom-built solutions because businesses can leverage AI-powered automation without needing AI expertise. This typically means a faster time to market, a lower total cost of ownership, and allowing for ongoing innovation.
With over 1000 Robovision-powered machines deployed across six continents, the Robovision AI Platform has become the go-to computer vision AI platform for machine builders and factory owners alike.
The AI Platform of Choice for Machine Builders & Factory Owners
Embracing Change
Whether variations in SKU type, shifts on the machine floor or a need to track new defects: change is constant in demanding production environments. Our platform helps you manage changes without additional effort from data scientists or developers.
Minimizing Downtime
Downtime is costly. Imagine using a platform to streamline AI lifecycle management by capturing data without interruption and maintaining vision AI accuracy. The Robovision AI Platform can while reducing the need for constant data science intervention.
Effortless AI Lifecycle Management
AI models can become inaccurate over time due (data drift) and production requirements evolve. That’s why it's ideal to have everything from data collection to training, analytics and retraining managed in one environment: the Robovision AI Platform.
Empowering Operators
Our award-winning interface empowers operators (the true product and process experts) to easily retrain models whenever needed.This impacts Operational Equipment Effectiveness (OEE), production yield, and cycle time.
Fewer Burdens for Data Scientists
For greater business impact, data scientists develop working AI models using algorithms, mathematics, and statistics as the foundation for effective AI applications. Once models are launched and working, data scientists can move on to new challenges, because with the Robovision AI Platform, AI retraining and continuous optimization require no additional data science input.
Break Down Silos
The Robovision AI Platform promotes collaboration. By bridging the gap between technical and non-technical team members, our platform streamlines workflow and maximizes productivity.
Maintainability and Scalability
A robust infrastructure allows for seamless scalability; grow business without compromising performance.
Access to Expertise
Businesses gain access to a vast supply of expert resources—as well as ongoing support—ensuring faster ROI and an optimized AI implementation.
The Robovision AI Platform was developed based on extensive experience in large-scale and unpredictable production environments. After more than a decade of implementing computer vision AI solutions across the world, two main success criteria emerged: computer vision AI implementations require reliable data and should be easy to maintain.
The Robovision computer vision AI platform tackles these challenges—and is user-friendly, too.
- Data Import
- Upload compressed folders automatically tagged with metadata
- Customizable importer tailored to specific company workflows
- Metadata like Process ID or Device ID included for seamless integration
- Easily searchable & filterable
- Data Annotation
- Advanced annotation tools, including single and multiview labeling
- GrabCut and Magnetic Lasso for fast segmentation
- Filtering options based on user, date, or review status metadata
- Predictive Annotator for AI-assisted labeling of new data (with user adjustments)
- Confusion matrix for annotation comparison
- Data Curation
- Tagging and filtering based on metadata to organize and inspect data, plus
- Training data analytics ensure class balance with graphical class distribution analysis
- Auto training/validation set creation with stratified splitting for balanced class representation
- Ground truth selection supports flexible strategies: selecting last updated annotations, annotations by specific users, manual selection, or random sampling
- Immutable training datasets with fixed links to select ground truth annotations
- Model Training
- Interactive progress monitor for real-time visualization of training metrics
- Supports hyperparameter tuning
- Configure to industry-standard parameters: early stopping, input resolution, batch size, learning rate, and more with Default or Expert mode
- Transfer learning capabilities to other users to improve existing models by training with additional datasets.
- Assess multiple models based on performance, parameter settings, and the datasets used with detailed trained model comparison
- Model Testing
- Evaluate new model performance against the ground truth.
- Robust model performance evaluation
- Assess models against annotated test sets or specific user inputs
- Supports test comparison; select the best model by comparing same dataset performance with multiple models
- Model self-check feature allows the model to test its validation data
- Identify outliers and potential label impurities for higher model accuracy and data quality
- Model Optimization
- Improve classification performance with optimized resource management.
- Powerful model optimization tools
- Can classify uncertain samples into an “unknown” class, protecting against model drift; triggers model maintenance when the “unknown” ratio becomes high
- Platform includes class confidence threshold optimization
- Set thresholds per class to identify valuable samples for re-labeling post-inference
- Model confidence threshold optimization adjust overall confidence levels based on available manual classification capacity
- Model Deployment
- Model performance and reliability in a variety of production environments.
- For running inference: flexible deployment options, centrally or on fab floor
- Configure parameters and choose deployment options
- With Model Inference feature, send new samples and receive predictions via API endpoint
- Model Monitor offers detailed reporting, tracking metrics like “unknown” rate and identifies low-confidence samples
Computer Vision AI Automation
At Robovision, we developed a computer vision AI platform to drive smart automation. Adding vision intelligence to machines creates a dramatic shift for industries, setting new standards for quality, efficiency, and productivity. Machine builders and their customers use the Robovision platform for demanding applications with high variability to realize better outcomes and consistent results.
What is Computer Vision AI?
Deep learning algorithms form the backbone of computer vision AI systems that learn and adapt to change. By adding a layer of vision intelligence, machines can process, analyze and interpret the visual world, much like humans. Through the Robovision AI platform, machines improve their performance over time and can carry out complex tasks such as:
- Classification
- Sorting
- Segmentation
- Object detection
- Anomaly detection
- 3D-handling
Computer vision AI systems extract information from images. Visual data can be derived from source material, such as medical scanning devices, live video sequences, 2D images, or multi-dimensional data created with 3D technologies.
Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) is everywhere: it writes emails, pilots cars and generates amazing art. While the term refers to machines simulating human intelligence, the label is broad and covers many subfields. One of those is Machine Learning, which involves training computers to learn from data and make predictions or decisions without needing explicit programming.
Traditional Computer Vision versus Computer Vision AI
Computer Vision systems can process and interpret visual data–images and videos–like humans do. Before the 2010s, Computer Vision applications relied on manual coding; data scientists determined every step of the process, this form of Computer Vision is neither intelligent nor dynamic.
With the rise of deep learning–an AI subfield with algorithms inspired by brain structure and functions–a new, more dynamic type of Computer Vision was born: one that makes it possible to generate algorithms with self-learning capabilities.
What does Computer Vision AI automation enable?
Computer vision AI goes beyond simply programming computers to follow instructions. Systems powered with Robovision’s computer vision AI software not only optimize as they learn, but also adapt to frequently changing requirements stemming from product variations, different sizing or new quality standards. All are crucial to industries needing mass customization, fast time-to-market, or stringent quality control.
Computer Vision AI: Trends and Challenges
Complex enterprise challenges—think the labor shortage and the reshoring trend in manufacturing, safety compliance in high-risk environments, or even limiting human error—can all be solved with computer vision AI automation. Computer vision algorithms can even analyze visual data with precision surpassing human capability. Accuracy and reliability are enhanced, product quality remains high and waste is reduced. Not to mention the boost in customer satisfaction.