Andi
Andi is an AI-driven conversational search engine designed to provide answers rather than links. It features an easy-to-use chatbot interface that delivers straightforward responses, locates top-quality information, and aids in maintaining online safety and productivity. It ensures privacy, operates without ads, and is available for anonymous use by everyone. By integrating language models and generative AI with real-time data, Andi formulates answers and offers explanations and summaries from premier sources. Additionally, Andi includes tools to combat spam and harmful content, offers a distraction-free reading mode for articles, and presents a visual search results page.
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This site provides an AI-driven platform enabling users to search for topics and protocols within episodes of The Huberman Lab and find answers to questions about science and health. Additionally, it offers timestamped YouTube links for the pertinent episodes. Users can also propose who should be featured in a future episode.
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Tavily AI is an automatic research assistant designed to conserve users' time and effort while exploring various topics. Users can submit their goals and queries, and the tool quickly delivers thorough, precise, and reliable research findings straight to their inbox. It's ideal for both personal and corporate use, and the research outcomes include source references.
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Aftercare is an AI-driven survey tool that aims to improve feedback gathering by converting standard surveys into engaging conversations. It employs smart AI follow-up questions to delve deeper into responses, revealing insights beyond initial answers. The platform includes an intuitive workflow builder with branching logic, enabling users to tailor survey paths and gain a thorough understanding of respondent experiences. Utilizing AI-based response categorization and analysis, Aftercare removes the requirement for manual data handling. Perfect for teams, it provides real-time adaptability, easy collaboration, and well-organized data, enhancing the efficiency and depth of feedback collection.