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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 Sixgill Sense?

The entire machine learning and computer vision workflow is simplified and accelerated through a unified no-code platform. Sense enables users to design and deploy AI IoT solutions in diverse settings, whether in the cloud, on-site, or at the edge. Learn how Sense provides simplicity, reliability, and transparency for AI/ML teams, equipping machine learning engineers with powerful tools while remaining user-friendly for non-technical experts. With Sense Data Annotation, users can effectively label video and image data, improving their machine learning models and ensuring the development of high-quality training datasets. The platform also includes one-touch labeling integration, which facilitates continuous machine learning at the edge and streamlines the management of all AI applications, thus enhancing both efficiency and performance. This all-encompassing framework positions Sense as an essential asset for a variety of users, making advanced technology accessible to those with varying levels of expertise. Additionally, the platform's flexibility allows for rapid adaptation to evolving project requirements and fosters collaboration among teams.

Media

Media

Integrations Supported

Integrations Supported

Check Point IPS
Check Point Infinity
ThreatStream

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard 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

Sixgill

Date Founded

2007

Company Location

United States

Company Website

sixgill.com

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
Labeling Quality
SDK
Task Management
Team Collaboration

Image Annotation

Not specified

IoT

Not specified

Machine Learning

Not specified

Video Annotation

Not specified

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