Best Text Mining Software

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.

spaCy is designed to help you do real work, build real products, or gather real insights. The library respects your time and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry standard with a huge ecosystem. Choose from a variety of plugins, integrate with your machine learning stack, and build custom components and workflows. Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking, and more. Easily extensible with custom components and attributes. Easy model packaging, deployment, and workflow management.

MeaningCloud is the easiest, most powerful, and most affordable way to extract the meaning from unstructured content: documents, articles, social conversations, web content, etc. We provide text analytics products to extract the most accurate insights from any content in many languages. And we do it SaaS and On-prem. We work for different industries (pharma, finance, media, retail, hospitality, telco, etc.) developing personalized and industry-oriented solutions.  Pay only for what you use, without any activation fees, minimum time commitment and with the most generous free plan of the market. If you don't like it, you can stop using it, just like that. Without software to install or infrastructure to deploy. All the reliability and scalability of solutions in the cloud, and the possibility of testing it for free.

Lettria offers a powerful AI platform known as GraphRAG, designed to enhance the accuracy and reliability of generative AI applications. By combining the strengths of knowledge graphs and vector-based AI models, Lettria ensures that businesses can extract verifiable answers from complex and unstructured data. The platform helps automate tasks like document parsing, data model enrichment, and text classification, making it ideal for industries such as healthcare, finance, and legal. Lettria’s AI solutions prevent hallucinations in AI outputs, ensuring transparency and trust in AI-generated results.

Komprehend AI APIs are the most comprehensive set of document classification and NLP APIs for software developers. Our NLP models are trained on more than a billion documents and provide state-of-the-art accuracy on most common NLP use cases such as sentiment analysis and emotion detection. Try our free demo now and see the effectiveness of our Text Analysis API. Maintains high accuracy in the real world, and brings out useful insights from open-ended textual data. Works on a variety of data, ranging from finance to healthcare. Supports private cloud deployments via Docker containers or on-premise deployment ensuring no data leakage. Protects your data and follows the GDPR compliance guidelines to the last word. Understand the social sentiment of your brand, product, or service while monitoring online conversations. Sentiment analysis is contextual mining of text which identifies and extracts subjective information in the source material.

All-in-one domain data source to get website logos, company data, categorization, and much more from a URL or email. Our website categorization API is highly accurate, a simple lookup of a company will classify its industry within 385 possible topic categories. Our classification taxonomy is based on the IAB V2 standard, it can be used for 1-1 personalization, marketing segmentation, online filtering, and more. Our classification taxonomy is based on the IAB V2 standard, it can be used for 1-1 personalization, marketing segmentation, online filtering, and more. We offer three top-level category structures to choose from. Whether you need the IAB taxonomy's deep categorization or prefer a more straightforward category structure, we’ve got you covered. Our website categorization API uses a machine learning (ML) engine to scan a website’s content and meta tags. It extracts text to classify the site and assigns up to three categories aided by natural language processing (NLP).

Find mentions of places, people, brands and events in documents and social media. Easily get additional data about the entities. Classify multilingual text into standard, pre-defined taxonomies or build your own custom classification scheme in minutes. Identify whether the expressed opinion in short texts (like product reviews) is positive, negative, or neutral. Automatically identify important, contextually relevant, concepts and key-phrases in articles and social media posts. Compare two texts and compute their syntactic and semantic similarity. Understand when two texts are about the same subject. Extract clean text article from newspapers, blogs and other websites. Remove boilerplate and advertising and get the article full text and images.

Allganize's industry-leading AI solutions provide businesses with the best tool to automate customer and employee support. Automate an average of 72% of all monthly support tickets within the first 4 months of implementation. Let our AI automate simple customer requests and free up your agents’ time to handle more complex issues. Employees can ask questions in a conversational way and find answers from multiple document types. Conversational AI chat bot pre-trained for your websites and automates customer service. Intelligent search that extracts accurate answers from any document, instantaneously. Automatically extracts important keywords from any document and categorizes them, providing valuable insights. Understands the context of product reviews using one's natural language to automatically detect positive or negative experiences. Assigns predefined categories from customer support conversions to accurately determine user intent.

The Moderation API automates text analysis using state-of-the-art artificial intelligence, so you can become more efficient, privacy-friendly, and scale faster.

Integrate our text analytics APIs to add world-leading NLP into your product, platform, or application. The most feature-complete NLP feature stack on the market, 19 years in development and constantly being improved with new libraries, configurations, and models. Determine whether a piece of writing is positive, negative, or neutral. Sort and organize documents into customizable groups. Determine the expressed intent of customers and reviewers. Find people, places, dates, companies, products, jobs, titles, and more. Deploy our text analytics and NLP systems across any combination of on-premise, private cloud, hybrid cloud, and public cloud infrastructure. Our core text analytics and natural language processing software libraries are at your command. Suitable for data scientists and architects who want complete access to the underlying technology or who need on-premise deployment for security or privacy reasons.

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required. There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale. Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data.