Best Text Analytics Software

Compare the Top Text Analytics Software as of October 2025

What is Text Analytics Software?

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 currently available using the table below. This list is updated regularly.

  • 1
    Kimola Cognitive
    Kimola Cognitive is a rock-solid Machine Learning Platform that enables users to grab reviews from 20+ channels and analyze + classify customer feedback -or any text data- automatically. Here are the TOP skills of Kimola Cognitive: - Scrape Web and Collect Reviews - Text Analysis with Entity Recognition - Analyze Data with Pre-Built models on Kimola Cognitive Gallery - Create, Train and Store Your Own Custom Models (No Coding Skills are Required) - Create Executive Summary, Generate SWOT Analysis and many powerful marketing materials using GPT Integration - Available in 6 languages (and counting!)
    Starting Price: $199 / 10000 Queries / month
  • 2
    Google Cloud Natural Language API
    Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.
  • 3
    Dovetail

    Dovetail

    Dovetail Research

    Dovetail is an AI-native customer intelligence platform that transforms customer conversations, documents, and surveys into actionable insights to drive better product decisions. It automatically analyzes call transcripts, survey responses, support tickets, and feedback to deliver fast, accurate reports that empower teams across product, marketing, sales, and customer experience. With integrations into Slack, Microsoft Teams, and popular tools like Notion and Zapier, Dovetail brings the voice of the customer directly to where teams work. The platform supports recruiting verified consumers and professionals for research, making customer feedback collection efficient and scalable. Trusted by Fortune 500 companies like Amazon, Deloitte, and Atlassian, Dovetail helps build a culture of customer-centricity through continuous insight sharing. Its AI-powered features reduce manual workload and accelerate understanding of user needs.
    Starting Price: $29/user/month
  • 4
    TextRazor

    TextRazor

    TextRazor

    The TextRazor API helps you extract and understand the Who, What, Why and How from your news stories with unprecedented accuracy and speed. Entity Extraction, Disambiguation and Linking. Keyphrase Extraction. Automatic Topic Tagging and Classification. All in 12 languages. Deep analysis of your content to extract Relations, Typed Dependencies between words and Synonyms, enabling powerful context aware semantic applications. Rapidly extract custom products, companies and build problem specific rules for tagging your content with your own categories. TextRazor offers a complete cloud or self-hosted text analysis infrastructure. We combine state-of-the-art natural language processing techniques with a comprehensive knowledgebase of real-life facts to help rapidly extract the value from your documents, tweets or web pages.
    Starting Price: $200 per month
  • 5
    Semantria

    Semantria

    Lexalytics

    Semantria is a natural language processing (NLP) API from Lexalytics, leaders in enterprise sentiment analysis and text analytics since 2004. Semantria offers multi-layered sentiment analysis, categorization, entity recognition, theme analysis, intention detection and summarization in an easy-to-integrate RESTful API package. Semantria is totally customizable through graphical configuration tools, supports 24 languages, and can be deployed across private, public and hybrid clouds. Semantria scales effortlessly from single servers to entire data centers and back again to meet your on-demand processing needs. Integrate Semantria to add powerful, flexible text analytics and natural language processing capabilities to your cloud-based data analytics products or enterprise business intelligence infrastructure. Or add Lexalytics storage and visualization tools to create a complete business intelligence platform for storing, managing, analyzing and visualizing text documents.
  • 6
    QCAmap

    QCAmap

    QCAmap

    QCAmap is an open access web application for systematic text analysis in scientific projects based on the techniques of qualitative content analysis. QCAmap can be used within research projects in e.g. psychology, sociology, education, economics, linguistic sciences, to analyze small and large amounts of any text material and images coming from interviews, group discussions, observation protocols, documents, open-ended questionnaire items and others. Qualitative Content Analysis is a strictly rule-guided procedure containing qualitative steps (assignment of categories to text passages and images) and quantitative steps (analysis of category frequencies). We have developed a web-based interactive software package, which leads you step by step through the different techniques of Qualitative Content Analysis. The software is free available. All your old projects are migrated to the new version and can be used as normal.
  • 7
    Gate

    Gate

    University of Sheffield

    If you need to solve a problem with text analysis or language processing, you're in the right place! GATE is an open source software toolkit capable of solving almost any text processing problem. It has a mature and extensive community of developers, users, educators, students and scientists. It is used by corporations, SMEs, research labs and Universities worldwide. It has a world-class team of language processing developers. GATE is open source free software, users can obtain free support from the user and developer community via GATE.ac.uk or on a commercial basis from our industrial partners. We are the biggest open source language processing project with a development team more than double the size of the largest comparable projects (many of which are integrated with GATE2). More than €5 million has been invested in GATE development3, our objective is to make sure that this continues to be money well spent for all GATE's users.
  • 8
    Cauliflower

    Cauliflower

    Cauliflower

    Whether for a service or a product, whether a snapshot or monitoring over time - Cauliflower processes feedback and comments from various application areas. Using Artificial Intelligence (AI), Cauliflower identifies the most important topics, their relevance, evaluation and relationships. In-house developed machine learning models for the extraction of content and evaluation of sentiment. Intuitive dashboards with filter options and drill-downs. Use included variables for language, weight, ID, time or location. Define your own filter variables in the dropdown. Cauliflower translates the results into a uniform language if required. Define a company-wide language about customer feedback instead of reading it sporadically and quoting individual opinions.
  • 9
    Relative Insight

    Relative Insight

    Relative Insight

    With a background in protecting children online, our comparative text analysis platform extracts business value from your text data. Relative Insight’s technology helps marketing insights professionals and brand specialists like you extract more value out of the text data you’ve already got. By utilizing a comparative approach, our platform helps you to generate rich audience insights quickly and at scale. This adds sophistication and science to your qualitative analysis. Equipped with unique marketing insights, brands can develop sharper communications, better brand positioning, and more resonant campaigns. Our platform will help you decipher and embrace your unstructured data and reduce the time it takes to analyze. This same approach can be used to analyze other primary research transcripts including videos, interviews, and focus groups, you’re sitting on a data goldmine! Relative Insight enables you to compare your brand messaging against competitors.
  • 10
    OpenText Unstructured Data Analytics
    OpenText™ Unstructured Data Analytics products employ AI and machine learning to help organizations uncover and leverage key insights stored deep within their unstructured data, including text, audio, video, and images. Organizations can connect all their data to understand the context and information locked inside high-growth unstructured content—at scale. Discover insights hidden within all types of media with unified text, speech, and video analytics that support more than 1,500 data formats. Use natural language processing, optical character recognition (OCR), and other AI-powered models to understand and track the meaning within unstructured data. Employ the latest innovations in machine learning and deep neural networks to understand written and spoken language in data, revealing greater insights.
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