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Azure Text Analytics

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What is Gavagai?

Our cutting-edge natural language processing technology utilizes artificial intelligence to gather, examine, and present insights from various types of customer communications. This encompasses everything from call transcripts, chat logs, emails, support inquiries, return requests, social media engagements, to surveys, all available in 47 languages. With our Explorer tool, users can swiftly evaluate open-ended text feedback within mere minutes. Furthermore, Explorer is equipped with an API that facilitates the effortless integration of unstructured text data into your business intelligence frameworks. The domain of employee experience is centered on evaluating and pinpointing the factors that enhance employee satisfaction and drive motivation. Our solutions enable organizations to effectively manage, analyze, and interpret large volumes of unstructured natural language information in significantly less time than typical methods. Designed for ease of use, the platform allows you to develop custom bots that cater to your unique business needs without requiring any programming skills. Immediate enhancements in operational efficiency can be realized just minutes after setup. In addition, the Gavagai API offers a comprehensive set of semantic analysis tools supporting 47 languages, granting users instant access to intuitive endpoints. This powerful functionality ensures that organizations can capitalize on insights drawn from their data, thereby improving their decision-making processes and fostering a more engaged workforce. Ultimately, by leveraging these advanced technologies, businesses can not only enhance customer communication but also significantly boost overall productivity and employee engagement.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.