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Asking Chat GPT for movie recommendations? Try Deep Search.

Find movies based on plot, theme, character, and much more.

The world is changing with the arrival of product-style AI tools. In recent days, text generative AI products like Jasper, GPT-3, Notion AI, and many others have been the buzz among both professionals and non-professionals alike. Other AIs like Midjourney and Dall-E that produce AI images from text are also very popular among the public for its ability to create stunning, creative images from very simple to complicated prompts. Generative AI is a fun tool when it comes to creating text or images, especially because of how little time it takes for the tools to create content.

However, there are other AI tools that solve more practical issues. Search and recommendation AI is one example that is applicable in daily life, which allows its users to navigate through inventories and find recommended content with ease.

Recommender AIs understand relationships between words, products, and attributes making it possible to give relevant and similar results. Though this may not be as “creative” in generating new concepts, recommendation Ais are trained to understand vertical-specific semantic meaning, which is one of the most fundamental parts of human language that make communication more natural.

Movie Deep Search is a recommendation AI that allows you to search for movies and TV shows using specific and detailed search queries. It also allows you to find movies according to its plot, lighting, soundtrack, and even character personality or appearance.

The practical problems with existing search and recommendation found on platforms is that they are limited to searching by title, cast, or genre. With Deep Search, you can look for movies that you only partially remember, or discover new movies based on your previous favorites.

Some features of Deep Search include searching with natural language, adding text to your search queries, customizing the weight of preferences, and filtering movies by meta filters like streaming service, release date, and genre. It is formed especially for video content like movies and TV, using information not only from productions but from real movie enthusiasts- making the search units even more colorful and diverse than ever.

Recommendation AIs are designed to give practical solutions to personalization. Its algorithms and units are focused on specific industries, sorting prompts into detailed categories according to its industry. The AI models and data ensure that you are given the most relevant, in-depth recommendations for your needs.

Movie Deep Search is built on datasets that target the movie industry in particular. Its categories include but are not limited to categories like Climax, Concept, Editing, Visual, Acting, Emotional Response, and so on. With Deep search, you will be able to find the deepest insights into your favorite movies and discover new movies that suit your preferences.

You can save time by quickly navigating through thousands of movies from all around the world. Unlike other generative models, you can also configure your search range by setting attributes with a higher weight to better match your personal preferences.

Better yet, it doesn’t require having to study or rewrite prompts and descriptions! With deep insight into movies, content, and semantics, Movie Deep Search is also updated live, and understands the world’s newest trends and give relevant propositions accordingly.

Deep Search is created by a series of ML and NLP algorithms that not only understand human language, but also slang, typos, and homonyms. It sorts through different categories and instances where words can be used, giving you results you want- understanding your search intent, like a human would.

Movie Deep Search is the fastest and most flexible choice when it comes to providing reliable, non-biased recommendations for specific movies. You can try out Deep Search this February, through our official website or join the community through Product Hunt!

Deep Search launched this February 19th and was named the #1 Best Rated Product of February. View our community, give us some feedback, and share your ideas with the group.



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