OpenText Intelligent Classification uses AI and machine learning to analyze and classify unstructured content at scale. It extracts context, applies text analytics, identifies key insights, and supports better decision-making and governance. This text-mining tool also helps organizations reduce manual effort, improve compliance, and unlock value from growing volumes of unstructured data by automating content understanding.
- 80% of enterprise data is unstructured
Tap into this underutilized data with powerful text mining tools for actionable insights.
- 70% reduction in classification time
Cut the time spent sorting and tagging documents with AI-driven automation, freeing up resources for higher-value tasks.
- 90%+ accuracy in entity and sentiment extraction
Precisely identify key entities, topics, and sentiment in multiple content types and languages with advanced NLP models.
Text auto-classification
Indexes and sorts stored documents with AI-generated classifications and relevancies. It enriches new content with in-place metadata to aid records management and improve findability.
Image and video analysis
Provides powerful NLP, Natural Language Understanding (NLU), and computer-vision technologies that go beyond text to analyze visuals, whether in dedicated image files or embedded within documents.
Concept extraction
Automatically extracts core concepts using algorithms to identify meaningful terms and noun phrases from documents.
Sentiment, emotion, and intention analysis
Detects whether documents convey a positive, negative, or neutral tone, are objective or opinion-based, how much emotion they express (like joy, anger, or trust), and the intent behind their message.
Language detection and multilingual processing
Automatically applies NLP and out-of-the-box annotators for ten languages and supports basic concept and named-entity extraction for 25 others.
Composite AI
Combines multiple AI and machine-learning techniques to maximize relevance of automated classification and categorizations. Enables IT to tune the composite AI rules and integrate external AI models.
Data analytics
Extract valuable insights using text mining, sentiment analysis, and advanced analysis.
| Concept extraction | Named entity recognition | Text classification and summarizer | Sentiment and emotion analysis | Language detection |
|---|---|---|---|---|
| Add On | OpenText Data Discovery |
Data integration and connectivity
Easily connect to various data sources and knowledge bases in easy-to-use interface.
| Multiple data connections | Categorizer knowledge bases | Add On | OpenText Analytics Database|
Data visualization and UX
Easily connect to various data sources and knowledge bases in easy-to-use interface.
| Intelligent Classification Studio | Add On | OpenText Intelligence || | Add On | OpenText Intelligence Aviator ||
Deployment options
| Off cloud | Private cloud |
Deployment
Explore scalable and flexible deployment options for global organizations of any size.
- Unlock the value of the cloud while maintaining control and compliance
Private cloud
Services
Accelerate digital transformation with guidance from certified experts.
- Modernize your information management with certified experts
Professional Services
- Turn support into your strategic advantage
Support Services
- Meet business goals with expert guidance, managed services, and more
Customer Success Services
- Free up your internal teams with expert IT service management
Managed Services
Canadian government gains valuable AI-driven insights and promotes transparency.
US county optimizes email management to enhance public service and compliance.
What types of unstructured data can OpenText Intelligent Classification analyze?
We can process a wide range of content, including emails, documents, PDFs, social media posts, customer feedback, call transcripts, and more—helping extract meaning and insights from text-heavy sources.
How does text mining software improve decision-making and governance?
By using AI and natural language processing, OpenText Intelligent Classification uncovers key entities, sentiment, and topics hidden in unstructured content, enabling smarter decisions, faster response times, and stronger compliance with regulatory requirements.
What is text mining in data analytics?
Text mining in data analytics is the process of extracting meaningful information from unstructured text data using techniques such as NLP, machine learning, and statistics.
Text mining frees customer insights trapped in unstructured content
OpenText Intelligent Classification uses AI to transform unstructured data into actionable insights.
What’s the difference between data mining and text mining?
Data mining and text mining are often seen as complementary analytic processes but here’s how they differ.
Take the next step
Ready to uncover the insights hidden in your unstructured data? Discover how OpenText Intelligent Classification can help you automate analysis and drive smarter decisions.