Overview

OpenText™ Intelligent Classification (Magellan) uses AI and machine learning to transform unstructured content into insights, enabling better decision-making and information governance while freeing up resources and time. With OpenText Intelligent Classification, organizations understand the context and information locked inside high-growth unstructured content at scale.

How OpenText Intelligent Classification can benefit business

Discover insights and value from dark data

Unlock complex unstructured content quickly, consistently, and with a high degree of completeness to gain rich metadata and meaningful business insights.

Increase efficiency

Continually adapt AI to provide insights or take low-risk actions that enable employees to focus on high-value tasks for smarter and more efficient processes.

Optimize repositories

Identify redundant, outdated, and trivial (ROT) content to accelerate migrations, reduce storage costs, and improve content retrieval.

Understand behaviors

Leverage sentiment and intent analysis to find the meaning within communications and content, including an individual’s feelings or intention.

Empower global organizations and diverse workforces

Enable concept and entity extraction with multilingual NLP in nearly 40 languages, such as advanced NLP in English, Chinese, and German or concepts and names in Russian.

Maximize content analytics value

Use APIs to seamlessly integrate with eDiscovery, workforce automation, records management, and other uses of information management systems.

Why OpenText Intelligent Classification?

Knowledge-based AI out of the box

Easily integrate into existing analytics applications and customize using prebuilt, customizable NLP, NLU, audio, image, and video image AI models.

Cross-document analysis

Leverage natural language processing capabilities to efficiently subdocument, document, and cross-document analysis for a holistic view of organizational content.

All-in-one AI solution for analytics

Make analysis easy with one solution that uses NLP for text and AI for video and images to auto-classify content and recognize relationships and sentiment.

Key features

Text auto-classification

Indexes and sorts stored documents with AI-generated classifications and relevancies and enriches new content with in-place metadata to aid records management and findability.

Image and video analysis

Provides powerful NLP, NLU and computer-vision technologies that go beyond text and analyze visuals, whether in dedicated image files or embedded within documents.

Concept extraction

Uses algorithms that automatically extract core concepts to identify meaningful terms and noun phrases from documents.

Sentiment, emotion, and intention analysis

Detects if documents convey a positive, negative or neutral tone, are objective or opinion-based, the extent to which they express emotions, such as joy, anger or trust, and the causal or business intent behind the message.

Composite AI

Combines multiple AI and machine learning techniques to maximize relevance of automated classification and categorizations and enable IT to tune the composite AI rules and integrate external AI models.

Language detection and multilingual processing

Automatically applies natural language processing and out-of-the-box annotators for ten languages and supports basic concept and named entity extraction for 25 others.