Textalytic Reviews

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.

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.