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Average Ratings 0 Ratings
Description
Kognic presents a state-of-the-art annotation platform tailored for sensor-fusion data, with the goal of minimizing both annotation time and expenses while ensuring premium quality results. This platform caters to a wide range of data labeling requirements, addressing everything from straightforward static objects to intricate scenarios, and includes features for 2D/3D objects, 2D instance segmentation, and free space annotations. One of its standout features is the co-pilot functionality, which utilizes imported predictions to automate processes, thereby cutting down annotation time by as much as 68% while still upholding quality standards. This automated approach allows for more effective human feedback where it truly counts, enhancing overall efficiency. In addition, Kognic places a strong emphasis on refining essential data to boost AI effectiveness, incorporating intelligent sorting based on model confidence and loss metrics, advanced filtering capabilities for both predicted and annotated objects, and seamless data chunk creation for focused reviews. Designed with enterprise needs in mind, Kognic is built to support missions at a global scale, making it a robust solution for organizations seeking to optimize their data annotation processes. By streamlining these processes, Kognic not only enhances productivity but also helps drive innovation in AI applications.
Description
Accelerate your team's NLP data labeling with our AI-powered platform, LightTag, which effectively organizes your workforce, allowing you to concentrate on what truly matters. The platform is designed to function seamlessly, enhancing efficiency through its intuitive interface.
Boost Your Productivity with Our Advanced Features:
- Convenient Keyboard Shortcuts
- Elimination of tokenization assumptions
- Comprehensive Unicode Support
- Annotations for subwords and phrases
- Support for RTL and CJK languages
- Annotations for Entities, Classifications, and Relations
LightTag's Review Mode and Reporting tools facilitate the creation of flawless datasets while ensuring that your annotators reach their peak performance. The AI within LightTag adeptly learns to provide high-accuracy predictions, automating basic labeling tasks, which enables your team to focus on generating more detailed and superior quality labels. Remarkably, 50% of the annotations generated within LightTag stem from our AI's suggestions, covering any language of your choice! Additionally, you can enhance suggestions by integrating your own models, using regular expressions, and employing dictionaries. Utilize our review functionality to swiftly validate your models and kickstart any project with confidence. This streamlined approach not only saves time but also elevates the overall quality of your data.
API Access
Has API
API Access
Has API
Integrations
Cogito
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$100 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Kognic
Founded
2018
Country
Sweden
Website
www.kognic.com
Vendor Details
Company Name
LightTag
Founded
2018
Country
Germany
Website
www.lighttag.io
Product 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
Product 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