AI for technology leaders. Make your AI developments perform in everyday life.

AI at Scale! provides leading scalable and versatile AI solutions to ensure the success of your algorithms, through a set of APIs and SDKs that let developers access state-of-the-art AI and easily build AI-powered applications.

Conversational AI Conversational AI is a service for creating speech and text dialogue interfaces. Start asking questions and quickly get answers from a wide range of domains, such as sports, stock market, restaurants, and events.

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Recommendation and Predictive AI provides general purpose solutions for anticipating user preferences and tailoring recommendations. With, you can include personalized, ad hoc recommendations made by AI models in your products and services.

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Privacy AI

The Federated Learning and Differential Privacy Framework has been developed to facilitate open research in the field, with the objective of building models that learn from decentralized data, preserving data privacy. It is an open-source framework and supports 100 percent of the AI algorithms used in industry.

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Use Cases: From Lab to Life is powerful and proven AI technology. With, you can create your own assistant by choosing the areas of knowledge (domains) that you want it to know. For example, a car manufacturer could have installed in its vehicles, in order to allow users to find nearby restaurants or gas stations; or a travel agency’s website could recommend activities to users, based on their destination.

Build a smart speaker with

Make use of's technology, including NLP, to analyze massive amounts of data concepts (not keywords!), significantly faster.

Recommend music, TV, movies, news, and more with

Easily create a music or movie recommender with Recommendation and Predictive AI.

Predict users’ next location and save them time with

Give your users information about travel time, nearby places, and make their journey easier.

Protect the privacy of your users' data with the Federated Learning and Differential Privacy Framework

With the Federated Learning and Differential Privacy Framework, sensitive data is processed on the device and never leaves it, ensuring privacy.


Tom Gruber on the Next Generation of Virtual Assistants

John Sculley on’s Predictive Analytics and Privacy AI

Tom Gruber says is “Leading the Way” in Privacy

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