Average Ratings 0 Ratings
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
AI is today blocked by a lack of labeled data. Not models. The first data-centric AI platform powered by a programmatic approach will unblock AI. With its unique programmatic approach, Snorkel AI is leading a shift from model-centric AI development to data-centric AI. By replacing manual labeling with programmatic labeling, you can save time and money. You can quickly adapt to changing data and business goals by changing code rather than manually re-labeling entire datasets. Rapid, guided iteration of the training data is required to develop and deploy AI models of high quality. Versioning and auditing data like code leads to faster and more ethical deployments. By collaborating on a common interface, which provides the data necessary to train models, subject matter experts can be integrated. Reduce risk and ensure compliance by labeling programmatically, and not sending data to external annotators.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Dask
No
Kubernetes
No
TensorFlow
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Kognic
Founded
2018
Country
Sweden
Website
www.kognic.com
Vendor Details
Company Name
Snorkel AI
Founded
2019
Country
United States
Website
snorkel.ai/
Product Features
Data Labeling
Human-in-the-loop
No
Labeling Automation
No
Labeling Quality
No
Performance Tracking
No
Polygon, Rectangle, Line, Point
No
SDK
No
Supports Audio Files
No
Task Management
No
Team Collaboration
No
Training Data Management
No
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
No
For Sales
No
For eCommerce
No
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No
Data Labeling
Human-in-the-loop
No
Labeling Automation
No
Labeling Quality
No
Performance Tracking
No
Polygon, Rectangle, Line, Point
No
SDK
No
Supports Audio Files
No
Task Management
No
Team Collaboration
No
Training Data Management
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No