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What is Snorkel AI?

The current advancement of AI is hindered by insufficient labeled data rather than the models themselves. The emergence of a groundbreaking data-centric AI platform, utilizing a programmatic approach, promises to alleviate these data restrictions. Snorkel AI is at the forefront of this transition, shifting the focus from model-centric development to a more data-centric methodology. By employing programmatic labeling instead of traditional manual methods, organizations can conserve both time and resources. This flexibility allows for quick adjustments in response to evolving data and business objectives by modifying code rather than re-labeling extensive datasets. The need for swift, guided iterations of training data is essential for producing and implementing high-quality AI models. Moreover, treating data versioning and auditing similarly to code enhances the speed and ethical considerations of deployments. Collaboration becomes more efficient when subject matter experts can work together on a unified interface that supplies the necessary data for training models. Furthermore, programmatic labeling minimizes risk and ensures compliance, eliminating the need to outsource data to external annotators, thus safeguarding sensitive information. Ultimately, this innovative approach not only streamlines the development process but also contributes to the integrity and reliability of AI systems.

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

Dask
Kubernetes
TensorFlow

Integrations Supported

Check Point IPS
Check Point Infinity
ThreatStream

API Availability

Has API

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
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Snorkel AI

Date Founded

2019

Company Location

United States

Company Website

snorkel.ai/

Company Facts

Organization Name

Sixgill

Date Founded

2007

Company Location

United States

Company Website

sixgill.com

Categories and Features

AI Development

Not specified

Data Annotation

Not specified

Data Labeling

Not specified

Machine Learning

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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