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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 Hive Data?

Create training datasets for computer vision models through our all-encompassing management solution, as we recognize that the effectiveness of data labeling is vital for developing successful deep learning applications. Our goal is to position ourselves as the leading data labeling platform within the industry, allowing enterprises to harness the full capabilities of AI technology. To facilitate better organization, categorize your media assets into clear segments. Use one or several bounding boxes to highlight specific areas of interest, thereby improving detection precision. Apply bounding boxes with greater accuracy for more thorough annotations and provide exact measurements of width, depth, and height for a variety of objects. Ensure that every pixel in an image is classified for detailed analysis, and identify individual points to capture particular details within the visuals. Annotate straight lines to aid in geometric evaluations and assess critical characteristics such as yaw, pitch, and roll for relevant items. Monitor timestamps in both video and audio materials for effective synchronization. Furthermore, include annotations of freeform lines in images to represent intricate shapes and designs, thus enriching the quality of your data labeling initiatives. By prioritizing these strategies, you'll enhance the overall effectiveness and usability of your annotated datasets.

Media

Media

Integrations Supported

Apache Atlas
Hive AutoML
Quickwork
Style Intelligence
Taxi for Email
Toad Intelligence Central
Wyn Enterprise
bipp

Integrations Supported

Apache Atlas
Hive AutoML
Quickwork
Style Intelligence
Taxi for Email
Toad Intelligence Central
Wyn Enterprise
bipp

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$25 per 1,000 annotations
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

Hive

Date Founded

2013

Company Location

United States

Company Website

thehive.ai/hive-data

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

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

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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