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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 Prodigy?

Groundbreaking machine teaching has arrived, featuring an incredibly effective annotation tool powered by active learning. Prodigy stands out as a customizable annotation platform so proficient that data scientists can take charge of the annotation process themselves, facilitating quick iterations. The progress seen in current transfer learning technologies enables the creation of high-quality models with minimal examples. By adopting Prodigy, you can fully harness modern machine learning strategies, engaging in a more adaptable approach to data collection. This capability not only speeds up your workflow but also grants you increased independence, resulting in a significant boost in project success rates. Prodigy combines state-of-the-art insights from both machine learning and user experience design, making it exceptionally versatile. Its continuous active learning framework ensures that you only annotate cases where the model exhibits uncertainty, optimizing your time and effort. The web application is not only robust and adaptable but also complies with the most up-to-date user experience standards. What makes Prodigy truly remarkable is its intuitive design: it allows you to focus on one decision at a time, keeping you actively involved—similar to a swipe-right method for data. Furthermore, this streamlined approach enhances the overall enjoyment and effectiveness of the annotation process, making it an invaluable tool for data scientists. As a result, users can expect not just efficiency but also a more satisfying experience while navigating through their annotation tasks.

Media

Media

Integrations Supported

Integrations Supported

ZenML

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$490 one-time fee
Per seat, available in packs of 5 seats

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

RoundSqr

Date Founded

2018

Company Location

India

Company Website

www.roundsqr.com/zastra/

Company Facts

Organization Name

Explosion

Date Founded

2016

Company Location

Germany

Company Website

prodi.gy/

Categories and Features

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

Data Annotation

Not specified

Data Labeling

Labeling Automation
Task Management

Image Annotation

Not specified

Machine Learning

Not specified

Video Annotation

Not specified

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