Best On-Premise Text Analytics Software of 2024

MeaningCloud is the easiest, most cost-effective, and most cost-effective way to extract meaning from unstructured content (articles, documents, social conversations, etc.). We offer text analytics products that provide the most accurate insights possible from any content in any language. We do it both SaaS-based and on-prem. We have worked in a variety of industries, including pharma, finance, media and retail. We develop tailored and industry-specific solutions. Our scenarios include: * Insight extraction * Analysis of the voice and opinions of the customer, employee or citizen. (User experience analytics and customer experience analytics in general. * Intelligent document automation Our APIs are free to use (20,000 API calls per year). Get our add-ins for Excel or Google sheets. Our integrations with Dataiku RapidMiner, Automation Anywhere, and Automation Anywhere as well as our SDKs (PHP, Python, Java and JavaScript) are available.

Natural language processing (NLP), which is a natural way to extract insights from unstructured text, is a great way to gain insight. To understand common topics and trends, identify key phrases and entities, such as people, places, or organizations. Pretrained models that are domain-specific can be used to classify medical terminology. Sentiment analysis allows you to gain a deeper understanding of customer opinions. You can evaluate text in many languages. Broad entity extraction Identify key concepts in text, including key words and named entities, such as people, places and organizations. Sentiment analysis that is powerful: Find out what customers think about your brand and how sentiment is around certain topics. Robust language detection: Assess text input in a variety of languages. Flexible deployment: Text Analytics can be run anywhere: on-premises, in the cloud, or at the edge with containers.

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.

PrepAI assists exam administrators and content leaders in saving time and reducing human error while generating question papers for online and offline exams. PrepAI offers support for state assessment, which boosts student achievement. The programs offer both realistic assessment exercises and consistent practice using artificial intelligence. The initiative aims at improving student learning in schools, edtech companies and educational institutions. Edtech professionals and innovative engineers developed our collaborative platforms and artificial intelligence platform. PrepAI uses Natural Language Processing technology for text analysis engine. This makes the evaluation more effective and has a greater impact on learning. PrepAI's product experts create the best solutions for individuals or organizations based upon their specific requirements. It also helps to create a rigorous study program that is aligned with standards that can better prepare students for success in the workplace.

Komprehend AI APIs provide the most complete set of document classification and NLP programming APIs for software developers. Our NLP models have been trained on more than a million documents and provide state of the art accuracy for most NLP use cases, such as sentiment analysis or emotion detection. Get our Text Analysis API free demo. It provides useful insights from textual data and maintains high accuracy in real life. It can work with a variety data types, from healthcare to finance. Private cloud deployments via Docker containers and on-premise deployments are supported. This prevents data leakage. Your data is protected and the GDPR compliance guidelines are followed to the letter. Monitor online conversations to understand the social sentiment surrounding your brand, product, and service. Sentiment analysis, also known as contextual mining of text, is a method that extracts and identifies subjective information from the source material.

TextGears provides translation, paraphrasing and text checking services for hundreds companies around the globe. Free demo available online. API allows to integrate TextGears text analysis into any modern software product. On-premise installation will be the best options for those companies that cannot use any services our of the corporate network. Supported languages include: English, French, German, Portuguese, Russian, Italian, Arabic, Spanish, Japanese, Chinese and Greek.

Integrate our text analytics APIs into your product, platform, and application to add world-leading NLP. This is the most complete NLP feature stack available. It has been 19 years in development and is constantly improving with new configurations, models, and libraries. You can determine whether a piece is positive, neutral, or negative. Sort and organize documents into configurable groups. Determine the intended purpose of customers and reviewers. Locate people, places and dates. Find companies, products, jobs, titles and more. Our text analytics and NLP systems can be deployed on any combination of public, private, hybrid, or on-premise cloud infrastructures. Our core text analytics and natural-language processing software libraries are available to you. This product is ideal for data scientists and architects who need to have full access to the underlying technology, or for on-premise deployment security or privacy reasons.

NLP software libraries and text analytics for on-premise integration or deployment. Integrate Salience in your enterprise business intelligence architecture, or white label it within your data analytics product. Salience can process 200 tweets per seconds while scaling from one process core to entire data centers with small memory footprint. For higher levels of ease, you can use Java, Python, C#, or the native C/C++ interface. You have full access to the technology. You can tune every text analytics function and NLP feature. This includes tokenization and part-of-speech tagging, sentiment scoring, categorization and theme analysis. Based on a pipeline model that includes NLP rules and machine-learning models. Identify where issues are occurring in the pipeline. You can adjust specific features without affecting the entire system. Salience runs entirely on your servers, but you can also offload sensitive data to the cloud servers.