Sentiment Search

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.

SentimentStack is an AI visibility platform designed to help brands track and improve their presence across major AI engines and search platforms. It monitors how often a brand appears in responses from systems like ChatGPT, Claude, Gemini, Perplexity, and Google. The platform provides real-time insights through metrics such as visibility scores, rankings, and competitive benchmarks. Users can analyze prompt performance and identify where competitors are outperforming them in AI-generated answers. Including a task list to improve your ai visibility, do-it yourself to improve ai visibility or SentimentStack can do it for you. Its knowledge context engine builds a centralized understanding of a brand, including products, personas, and messaging. The platform offers features like citation tracking, content audits, and automated alerts to maintain strong visibility. Overall, SentimentStack helps brands adapt to the growing importance of AI-driven search and discovery.