Discover the information that matters using natural language processing (NLP)

Screenshot of SAS Visual Text Analytics - visualize data with highlights

SAS Visual Text Analytics

Scale the human act of reading, organizing and extracting useful information from huge volumes of textual data.

Text analysis leader on G2

SAS Visual Text Analytics wins ‘Summer 2024 Leader in Text Analysis’ and ‘Summer 2024 Enterprise Leader in Text Analysis' badges from G2.

Organizations of all sizes are working smarter with SAS

Key features

Augment human efforts to analyze unstructured text with AI using a variety of modeling approaches. Experience the combined power of natural language processing, machine learning and linguistic rules.

Large Language Model (LLM)-based classification

Use linguistic models to curate the best data for LLM fine-tuning and RAG. Augment LLM content moderation to detect toxicity and bias and prevent private data leakage to improve LLM outcomes without modifying or impacting the LLM.

LLM calibration

Use linguistic models to curate the best data for LLM fine-tuning and RAG. Augment LLM content moderation to detect toxicity and bias and prevent private data leakage to improve LLM outcomes without modifying or impacting the LLM.

Trend analysis

Unsupervised machine learning groups documents based on common themes. Relevance scores calculate how well each document belongs to each topic, and a binary flag shows topic membership above a given threshold.

Information extraction

Pull out specific pieces of information or relationships between information from text using a powerful, flexible and scalable SAS proprietary programming language called language interpretation for textual information (LITI).

Hybrid modeling approaches

Build effective text models using a variety of combined capabilities, including a rich mix of linguistic rules, natural language processing, machine learning and deep learning.

Parsing

Text is separated into words, phrases, punctuation marks and other elements of meaning to provide the human framework a machine needs to analyze text at scale.

Corpus analysis

Understand corpus structure through easily accessible output statistics to leverage natural language generation (NLG) for tasks such as data cleansing, separating out noise, sampling effectively, preparing data as input for further models (rules-based and machine learning), and strategizing modeling approaches.

Native support for 33 languages

Out-of-the-box NLP functionality enables native language analysis using dictionaries and linguistic assets created by native language experts from around the world.

Recommended resources for SAS Visual Text Analytics

E-Book

Make Every Voice Heard With Natural Language Processing

Solution Brief

Natural language processing for government efficiency

Blog

SAS Blogs: Text Analytics

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