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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 RAIC?

Models can now be created, trained, and implemented within minutes rather than taking months to complete. Initiate your search by uploading just one image of an object, and RAIC will efficiently locate similar items within an unlabeled dataset. The findings are contextually related to the original image, enabling you to enhance AI performance through intuitive human feedback. You can categorize your data based on specific detection criteria, whether it's focused on a single item or multiple objects. Once items are contextually linked, RAIC empowers you to organize and classify them into distinct categories, facilitating the training process. Subsequently, RAIC will generate either a detection model or a classification model based on your selection of Quick Train for urgent needs or Deep Train for a more conventional, accuracy-focused approach when time constraints are less pressing. This flexibility allows users to tailor their training methods to best suit their project requirements.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

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

RAIC Labs

Date Founded

2019

Company Location

United States

Company Website

raiclabs.com

Categories and Features

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

Image Annotation

Not specified

Image Recognition

Not specified

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