Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
For nearly ten years, Babel Street has established itself as a frontrunner in the industry with its innovative AI-driven analytics platform, which equips teams with essential insights for effective analysis, strategic action, and achieving mission success on a unified interface. The company employs cutting-edge linguistics technology to extract and interpret actionable insights, acting as a significant force multiplier that supports customer initiatives globally. By swiftly enriching and transforming all publicly accessible or customer-supplied data, Babel Street ensures that valuable insights are readily available. Its AI-powered, persistent search capability spans over 200 languages worldwide, facilitating the discovery, enrichment, and translation of the most pertinent insights regardless of their source or language. Featuring one of the largest proprietary ontologies globally, the platform transcends basic machine translation, capturing critical nuances that enhance understanding. In addition, Babel Street's analytics platform serves as a comprehensive gateway that provides a seamless end-to-end experience for enriching digital data and converting it into actionable knowledge. With its commitment to innovation and excellence, Babel Street continues to redefine the landscape of data analytics.
Description
Developing a topic model from the ground up requires a high level of programming skill. This specialized knowledge can be costly and often overshadows the essential understanding of the data itself. The process of manually labeling your training data is not only time-consuming but also labor-intensive and expensive. Outsourcing this task to low-wage workers may expedite the process and reduce costs, yet it often sacrifices both accuracy and detail. Each of these methods results in a static taxonomy that can be challenging to adapt over time. It's crucial to transition away from mere tagging and empower subject matter experts to engage with their data for modeling and analysis. With vast amounts of text data at your disposal, brimming with insights ready for exploration, the need for effective tools becomes clear. Pienso is here to assist with this challenge by enabling you to train models using your own data, as we recognize that this approach yields the best results. Regardless of whether your data is unstructured, semi-structured, lengthy, or concise, Pienso is equipped to help you transform it into valuable insights that can drive decision-making. By leveraging Pienso, you can unlock the full potential of your data without the traditional hurdles associated with topic modeling.
API Access
Has API
No
API Access
Has API
No
Integrations
Intel 471 TITAN
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Babel Street
Country
United States
Website
www.babelstreet.com/platform
Vendor Details
Company Name
Pienso
Founded
2016
Country
United States
Website
www.pienso.com
Product Features
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No