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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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 

Screenshots View All

Screenshots View All

Integrations

Intel 471 TITAN Yes 

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 

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