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What is teX.ai?

In today's world of overwhelming content, your business can effectively pinpoint and handle only the text that truly matters to its operations. No matter the specific requirements of your organization, whether it’s enhancing operational agility or making quicker decisions, teXai—a company featured in Forbes for its innovative text analytics—empowers you to leverage text for business advancement. With its robust preprocessor engine, teXai can detect and extract relevant information from various documents found in your organization’s emails or text communications. This technology is also applicable for analyzing tables, emails, text messages, and extensive archives. Additionally, the intelligent and adaptable linguistic application can recognize different text genres, categorize similar content, and generate brief summaries, thereby equipping business teams with the essential context from pertinent text. Furthermore, the text analytics software streamlines the extraction of vital components from your text, making the decision-making process more straightforward and efficient. By integrating these tools, your organization can stay ahead in a rapidly evolving landscape.

What is SAS Text Miner?

SAS Text Miner facilitates the extraction of valuable insights from diverse text documents, uncovering hidden themes and concepts. This tool adeptly combines quantitative information with unstructured text, effectively blending text mining with traditional data mining techniques. Being a part of the SAS® Enterprise Miner suite, it requires that SAS Enterprise Miner is installed on the same system to function properly. Furthermore, SAS High-Performance Text Mining can run on both a grid of computers or a single machine with multiple CPUs, making it flexible for various computing environments. The text algorithms used are optimized for multi-threading and operate in memory, which greatly improves both speed and efficiency while reducing input/output load. Users can access SAS Text Miner as nodes within the SAS High-Performance Data Mining framework or through the procedures PROC HPTMINE and PROC HPTMSCORE. To better understand SAS technology, individuals can take advantage of training courses provided by analytics experts, which will help them attain a thorough grasp of the available tools. Gaining expertise in these areas not only boosts one’s analytical skills but also enhances overall capabilities in data mining and analysis methodologies. Ultimately, mastering these techniques can empower users to make more informed decisions based on data-driven insights.

Media

Media

Integrations Supported

Keras
Selenium
Smart City Solutions
TensorFlow

Integrations Supported

Keras
Selenium
Smart City Solutions
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

teX.ai

Date Founded

2019

Company Location

United States

Company Website

tex-ai.com

Company Facts

Organization Name

SAS Institute

Date Founded

1976

Company Location

United States

Company Website

support.sas.com/en/software/text-miner-support.html

Categories and Features

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and Features

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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