Compare Canvs vs. Google Cloud Natural Language API

Canvs AI is an insight platform that transforms open-ended texts from surveys, social media and transcripts into conversational intelligence. It can also be used to analyze product reviews and other information such as product reviews and product reviews. Canvs is used worldwide by some of the most respected brands, research agencies, media and entertainment companies to speed up time-to-insights and deepen understanding of audience. It also reduces the cost of analysis. Automate the analysis and interpretation of open-ended text to quickly uncover consumer insights with deep emotional context and high analytical confidence. Canvs' intuitive and easy-to-use insights portal allows you to quickly explore, filter and compare your findings. You can also generate stunning data visualizations. Automate the coding of attribute, recall, and awareness questions. Quickly identify and categorize sentiments and emotions associated with respondents and responses.

Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.