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What is Kognic?

Kognic offers an advanced annotation platform specifically designed for sensor-fusion data, aiming to significantly reduce both the time and cost associated with data labeling while delivering high-quality outcomes. This versatile platform meets a diverse array of data labeling needs, ranging from basic static objects to complex scenarios, and features capabilities for handling 2D and 3D objects, 2D instance segmentation, as well as free space annotations. A notable attribute of this platform is the co-pilot functionality, which leverages imported predictions to automate various tasks, resulting in a potential reduction of annotation time by up to 68% without compromising quality. This automation not only streamlines processes but also allows for more meaningful human feedback where it is most impactful, improving overall operational efficiency. Furthermore, Kognic prioritizes the enhancement of critical data to increase the effectiveness of AI, employing intelligent sorting based on model confidence and loss metrics, advanced filtering options for both predicted and annotated entities, and seamless data chunk generation for concentrated reviews. Tailored for enterprise requirements, Kognic is designed to support large-scale operations globally, providing a powerful solution for organizations eager to refine their data annotation workflows. By optimizing these workflows, Kognic not only boosts productivity but also fosters innovation within the realm of AI applications, paving the way for advancements in technology. As a result, organizations can leverage this platform to maintain competitive advantages in an ever-evolving data landscape.

What is Amazon SageMaker Ground Truth?

Amazon SageMaker offers a suite of tools designed for the identification and organization of diverse raw data types such as images, text, and videos, enabling users to apply significant labels and generate synthetic labeled data that is vital for creating robust training datasets for machine learning (ML) initiatives. The platform encompasses two main solutions: Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, both of which allow users to either engage expert teams to oversee the data labeling tasks or manage their own workflows independently. For users who prefer to retain oversight of their data labeling efforts, SageMaker Ground Truth serves as a user-friendly service that streamlines the labeling process and facilitates the involvement of human annotators from platforms like Amazon Mechanical Turk, in addition to third-party services or in-house staff. This flexibility not only boosts the efficiency of the data preparation stage but also significantly enhances the quality of the outputs, which are essential for the successful implementation of machine learning projects. Ultimately, the capabilities of Amazon SageMaker significantly reduce the barriers to effective data labeling and management, making it a valuable asset for those engaged in the data-driven landscape of AI development.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
ZenML

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.08 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Kognic

Date Founded

2018

Company Location

Sweden

Company Website

www.kognic.com

Company Facts

Organization Name

Amazon Web Services

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/es/sagemaker/data-labeling/

Categories and Features

Data Labeling

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

Categories and Features

Data Labeling

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

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