Best Text Analytics Software for C
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Compare the Top Text Analytics Software that integrates with C as of June 2025
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This a list of Text Analytics software that integrates with C. Use the filters on the left to add additional filters for products that have integrations with C. View the products that work with C in the table below.
What is Text Analytics Software for C?
Text analytics software is a type of software used to extract and analyze data from text-based sources. It can be used to uncover meaningful patterns, trends, and insights from large amounts of unstructured data. Text analytics software typically combines natural language processing (NLP) and machine learning techniques to identify desired entities such as people, organizations, locations, topics, or sentiment. This technology can be used in a variety of industries such as healthcare, retail, finance and marketing for purposes like customer feedback analysis or opinion mining. Compare and read user reviews of the best Text Analytics software for C currently available using the table below. This list is updated regularly.
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Hyland Document Filters
Hyland Software
Document Filters is an SDK that can be leveraged for various applications, such as content indexing, e-discovery, data migration, feeding data into AI/ML models and much more by extracting data from unstructured sources. It gives software developers the ability to perform deep inspection, data extraction, output manipulation and conversion for virtually any type of document and language. -
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Salience
Lexalytics
Text analytics and NLP software libraries for on-premise deployment or integration. Integrate Salience into your enterprise business intelligence architecture or white label it inside your own data analytics product. Salience can process 200 tweets per second while scaling from single process cores to entire data centers with a small memory footprint. Use Java, Python, .NET/C# bindings for higher level ease or the native C/C++ interface for maximum speed. Enjoy full access to the underlying technology. Tune every text analytics function and NLP feature, from tokenization and part of speech tagging to sentiment scoring, categorization, theme analysis, and more. Built on a pipeline model of NLP rules and machine learning models. When issues arise, see exactly where they are in the pipeline. Adjust specific features without disrupting the larger system. Salience runs entirely on your servers while staying flexible enough to offload insensitive data to cloud servers.
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