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Average Ratings 0 Ratings
Description
A powerful labeling platform for all stages and types of ML development. We leverage a suite of industry-leading computer vision algorithms to automatically detect and classify the content of your images and videos. Creating detailed segmentation information is a time-consuming process. Machine assistance speeds up task completion by as much as 70%, saving you both time and money. We leverage ML to propose labels that accelerate human labeling. This includes computer vision models to automatically detect, localize, and classify entities in your images and videos before handing off the task to our workforce. Automatic labelling reduces workforce costs and allows annotators to spend their time on the more complicated steps of the annotation process. Our video annotation tool is built to handle 4K resolution and long-running videos natively and provides innovative features like interpolation, object proposal, and entity resolution.
Description
Revolutionary machine teaching is here with an exceptionally efficient annotation tool driven by active learning. Prodigy serves as a customizable annotation platform so effective that data scientists can handle the annotation process themselves, paving the way for rapid iteration. The advancements in today's transfer learning technologies allow for the training of high-quality models using minimal examples. By utilizing Prodigy, you can fully leverage contemporary machine learning techniques, embracing a more flexible method for data gathering. This will enable you to accelerate your workflow, gain greater autonomy, and deliver significantly more successful projects. Prodigy merges cutting-edge insights from the realms of machine learning and user experience design. Its ongoing active learning framework ensures that you only need to annotate those examples the model is uncertain about. The web application is not only powerful and extensible but also adheres to the latest user experience standards. The brilliance lies in its straightforward design: it encourages you to concentrate on one decision at a time, keeping you actively engaged – akin to a swipe-right approach for data. Additionally, this streamlined process fosters a more enjoyable and effective annotation experience overall.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Amazon S3
Yes
Azure Storage
Yes
Google Cloud Storage
Yes
ZenML
No
Integrations
Amazon S3
No
Azure Storage
No
Google Cloud Storage
No
ZenML
Yes
Pricing Details
$5000
Hourly rates for Control SaaS and Alegion Managed Platform offerings. Hourly, per project, and per annotation pricing model options for Fully Managed Labeling Services.
Free Trial
Yes
Free Version
No
Pricing Details
$490 one-time fee
Per seat, available in packs of 5 seats
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Alegion
Founded
2014
Country
United States
Website
www.alegion.com
Vendor Details
Company Name
Explosion
Founded
2016
Country
Germany
Website
prodi.gy/
Product Features
Computer Vision
Blob Detection & Analysis
Yes
Building Tools
No
Image Processing
Yes
Multiple Image Type Support
Yes
Reporting / Analytics Integration
Yes
Smart Camera Integration
No
Data Labeling
Human-in-the-loop
Yes
Labeling Automation
Yes
Labeling Quality
Yes
Performance Tracking
Yes
Polygon, Rectangle, Line, Point
Yes
SDK
No
Supports Audio Files
Yes
Task Management
Yes
Team Collaboration
Yes
Training Data Management
Yes
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
Yes
Machine Learning
Yes
Visual User Interface
Yes
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
Yes
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
Yes
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
Yes
Sentence Segmentation
Yes
Stemming/Lemmatization
No
Tokenization
No
Product Features
Data Labeling
Human-in-the-loop
No
Labeling Automation
Yes
Labeling Quality
No
Performance Tracking
No
Polygon, Rectangle, Line, Point
No
SDK
No
Supports Audio Files
No
Task Management
Yes
Team Collaboration
No
Training Data Management
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No