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ease
features
design
support

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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

Utilizing Automaton AI's ADVIT platform, you can effortlessly create, manage, and enhance high-quality training data alongside DNN models, all from a single interface. The system automatically optimizes data for each stage of the computer vision pipeline, allowing for a streamlined approach to data labeling processes and in-house data pipelines. You can efficiently handle both structured and unstructured datasets—be it video, images, or text—while employing automatic functions that prepare your data for every phase of the deep learning workflow. Once the data is accurately labeled and undergoes quality assurance, you can proceed with training your own model effectively. Deep neural network training requires careful hyperparameter tuning, including adjustments to batch size and learning rates, which are essential for maximizing model performance. Additionally, you can optimize and apply transfer learning to enhance the accuracy of your trained models. After the training phase, the model can be deployed into production seamlessly. ADVIT also supports model versioning, ensuring that model development and accuracy metrics are tracked in real-time. By leveraging a pre-trained DNN model for automatic labeling, you can further improve the overall accuracy of your models, paving the way for more robust applications in the future. This comprehensive approach to data and model management significantly enhances the efficiency of machine learning projects.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 Yes 
Azure Storage Yes 
Google Cloud Storage Yes 

Integrations

Amazon S3 No 
Azure Storage No 
Google Cloud Storage No 

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

No price information available.
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 Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
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) Yes 
In Person Yes 

Vendor Details

Company Name

Alegion

Founded

2014

Country

United States

Website

www.alegion.com

Vendor Details

Company Name

Automaton AI

Founded

2019

Country

India

Website

automatonai.com

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 No 
Labeling Quality No 
Performance Tracking No 
Polygon, Rectangle, Line, Point No 
SDK No 
Supports Audio Files No 
Task Management No 
Team Collaboration No 
Training Data Management No 

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization 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 

Alternatives

Alternatives

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