Epigos AI is an advanced computer vision platform that empowers businesses to transform their operations and automate processes. The platform provides features like dataset management, image annotation, model training, and model deployment.
With the dataset management feature, users can easily organize, update, and access their data while efficiently handling large-scale datasets. The image annotation feature simplifies the data annotation process, allowing users to accurately and quickly label images.
The platform also caters to model training, providing cutting-edge algorithms to fine-tune models for optimal performance, along with hosted GPUs for cost-effective training.
The last feature is model deployment, where Epigos AI enables users to deploy their trained models as hosted API endpoints across different platforms such as NVIDIA Jetson, iOS devices, OAK cameras, Raspberry Pi, web browsers, and various cloud services.
Besides these, Epigos AI also offers a data labelling service where their expert team handles the task of data annotation, ensuring accurate and high-quality annotations.
Epigos AI is designed to support various industries in their AI journey and offers multiple other resources like documentation and API status for smooth operation.
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Pros & Cons
Dataset management feature
Efficient large-scale data handling
Quick image annotation
Accurate image labeling
Cutting-edge model training algorithms
Cost-effective GPUs for training
Diverse platform model deployment
Data labelling service available
Outputs hosted API endpoints
Deploy on NVIDIA Jetson
Deploy on iOS devices
Deploy on OAK cameras
Deploy on Raspberry Pi
Deploy on web browsers
Supports various cloud services
Detailed documentation
API status resource
Supports multiple industries
Easy data organization and updates
Optimized model performance
Professional data annotation service
View, sort, filter data
Auto label functionality
Bounding box annotations
Category annotation feature
Moderation process for annotation
SOTA models support
Tensorflow compatibility
Model library availability
Python and Node.js compatibility
Rest API for model deployment
Web UI for deployment
Edge device compatibility
Professional data labelers
Strict security standards
Industry-specific solutions
Version control for data
Support for enterprises, startups
Auto label feature
Model lifecycle management
Data annotation outsourcing service
Supports diverse model training
Annotate, train, deploy on same platform
Tailored model training
Automatic detection modelling
Deploy models with ease
Automated model fine-tuning
Support web based interfaces
Complete control of training data
Limited to specific platforms
No desktop application
No free version
Limited image annotation tools
Cannot handle 3D data
Limited model training options
Dataset versioning not specified
Requires knowledge of Python
No real-time performance tracking
No Android deployment
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