Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon SageMaker enables the identification of various types of unprocessed data, including images, text documents, and videos, while also allowing for the addition of meaningful labels and the generation of synthetic data to develop high-quality training datasets for machine learning applications. The platform provides two distinct options, namely Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which grant users the capability to either leverage a professional workforce to oversee and execute data labeling workflows or independently manage their own labeling processes. For those seeking greater autonomy in crafting and handling their personal data labeling workflows, SageMaker Ground Truth serves as an effective solution. This service simplifies the data labeling process and offers flexibility by enabling the use of human annotators through Amazon Mechanical Turk, external vendors, or even your own in-house team, thereby accommodating various project needs and preferences. Ultimately, SageMaker's comprehensive approach to data annotation helps streamline the development of machine learning models, making it an invaluable tool for data scientists and organizations alike.
Description
Our perspective on data is evolving, and at this moment, businesses are increasingly relying on trustworthy and precise transcription and data annotation services. We have developed a unique task distribution and workforce management platform that adheres to the highest standards of information security, ensuring that your data remains encrypted and safely handled. Our workflows comply with HIPAA and GDPR standards, and we provide customizable services, including the ability to geofence our workforce to designated areas. The technology and processes we have implemented allow us to consistently deliver top-notch data at competitive prices. For artificial intelligence and machine learning models to be effective, they need data that is tailored to specific use cases. With our expertise in assembling large teams of workers, we are capable of providing high-quality data for diverse applications, such as generating contact center interactions, images, review and survey data, and many other needs. This commitment to excellence positions us as a leader in the data services industry, ready to meet the demands of our clients.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Amazon SageMaker Unified Studio
Yes
ZenML
Yes
Integrations
Amazon SageMaker
No
Amazon SageMaker Unified Studio
No
ZenML
No
Pricing Details
$0.08 per month
Free Trial
No
Free Version
No
Pricing Details
$0.79 per minute
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
Yes
iPad App
Yes
Android App
Yes
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
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Amazon Web Services
Founded
2006
Country
United States
Website
aws.amazon.com/es/sagemaker/data-labeling/
Vendor Details
Company Name
TranscribeMe
Founded
2011
Country
United States
Website
transcribeme.com
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
Speech Recognition
Audio Capture
Yes
Automatic Form Fill
No
Automatic Transcription
Yes
Call Analysis
No
Concatenated Speech
No
Continuous Speech
No
Customizable Macros
Yes
Multi-Languages
Yes
Specialty Vocabularies
No
Speech-to-Text Analysis
No
Variable Frequency
No
Voice Recognition
Yes