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What is Zastra?

We are set to enhance the platform by adding annotation capabilities specifically designed for segmentation tasks. The Zastra repository will feature cutting-edge algorithms that streamline segmentation processes, thereby improving active learning across various datasets. To support this, we will implement complete end-to-end machine learning operations, which will include dataset and experiment version control, as well as templated pipelines that facilitate model deployment in standard cloud environments and on edge devices. By embedding advancements in Bayesian deep learning within the active learning framework, we aspire to significantly enhance overall performance. Additionally, we will improve the precision of annotations by utilizing specialized architectures like Bayesian CNNs, which will ensure superior outcomes. Our dedicated team has committed considerable time and resources to create this innovative solution tailored to your requirements. While we are consistently adding new features and improvements to the platform, we invite you to participate in a trial run soon! Zastra offers a variety of essential functionalities, such as active learning for object classification, detection, localization, and segmentation across multiple formats, including images, videos, audio, text, and point cloud data. This versatility not only makes Zastra a powerful tool for addressing a wide range of data challenges, but it also positions us well to adapt to future needs in data processing and machine learning advancements.

What is Alegion?

An advanced labeling platform designed for various stages and types of machine learning development is at your service. By utilizing a collection of top-tier computer vision algorithms, we can swiftly identify and categorize the content within your images and videos. Traditionally, creating thorough segmentation data has been a labor-intensive endeavor; however, our machine assistance can enhance productivity by up to 70%, ultimately conserving both time and financial resources. We harness machine learning to suggest labels that facilitate and expedite human labeling processes, employing computer vision models that can automatically detect, localize, and classify elements in your images and videos before passing the task to our skilled workforce. This approach to automatic labeling not only decreases labor costs but also allows annotators to focus on the more intricate aspects of the annotation process. Furthermore, our video annotation tool is engineered to natively support 4K resolution and lengthy videos, incorporating cutting-edge features such as interpolation, object proposal, and entity resolution, ensuring a comprehensive and efficient annotation experience. With our platform, you can achieve higher accuracy and efficiency in your machine learning projects.

Media

Media

Integrations Supported

Integrations Supported

Amazon S3
Azure Storage
Google Cloud Storage

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$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 Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

RoundSqr

Date Founded

2018

Company Location

India

Company Website

www.roundsqr.com/zastra/

Company Facts

Organization Name

Alegion

Date Founded

2014

Company Location

United States

Company Website

www.alegion.com

Categories and Features

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

Computer Vision

Blob Detection & Analysis
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration

Data Annotation

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Data Preparation

Data Transformation
Machine Learning
Visual User Interface

Image Annotation

Not specified

Machine Learning

Natural Language Processing (NLP)

Natural Language Processing

Named Entity Recognition
Part-of-Speech Tagging
Sentence Segmentation

Video Annotation

Not specified

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