OpenText Unstructured Data Analytics
OpenText™, Unstructured Data Analytics Products use AI and machine learning in order to help organizations discover and leverage key insights that are hidden deep within unstructured data such as text, audio, videos, and images. Organizations can connect their data at scale to understand the context and content locked in high-growth, unstructured content. Unified text, speech and video analytics support over 1,500 data formats to help you uncover insights within all types media. Use OCR, natural language processing and other AI models to track and understand the meaning of unstructured data. Use the latest innovations in deep neural networks and machine learning to understand spoken and written language in data. This will reveal greater insights.
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Semeon Analytics
Semeon helps you to understand and prioritize large-scale customer, employee, and marketplace feedback data from any source, including social, reviews, and CRM data. Our platform automatically extracts multi-word concepts relevant to your data, measures sentiment, and generates insightful dashboards. Semeon technology is available in more than 10 languages. Government entities, security and defense agencies, brands, and organizations around the globe rely on it to improve customer experience, citizens' lives, reduce operational costs, and drive growth.
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Google Cloud Natural Language API
Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.
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TextRazor
TextRazor API allows you to extract and understand the Whos, Whats, Whys and Hows from your news stories with unparalleled accuracy and speed. Entity Extraction, Linking, and Disambiguation. Keyphrase extraction. Automatic Topic Tagging, Classification. All this in 12 languages. Deep analysis of your content allows you to extract Relationships, Typed Dependencies between words, and Synonyms. This allows for powerful context-aware semantic applications. Rapidly extract custom products and companies, and create problem-specific rules to tag your content with your own categories. TextRazor provides a cloud-based or self-hosted text analysis platform. Our combination of state-of-the art natural language processing techniques and a vast knowledgebase of real-life facts allows us to quickly extract the value from your documents.
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