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Reply has built its own Robotics for Customers approach in the context of Data-Driven Customer Engagement. Robotics for Customers is a framework built on two foundational pillars: Recommendation Systems and Conversational Systems.
There is no mystery behind traditional collaborative algorithms: they simply try to suggest similar content to what we have previously watched, or what other users with similar tastes to us have been watching. Yet we can go even further using Deep Learning and Knowledge Graph methods that leverage contextual and unstructured data.
Reply has developed the framework Robotics for Customers which allows customers to build a time-to-value Recommendation System that can be easily integrated into any existing platform.
With the current hype on customer centricity going strong, a lot of companies are asking Reply to help them turn their product and service development towards a more human centered one.
In recent decades, we have witnessed the emergency of an increasingly robotic society and the growth of complex artificial intelligence. We are in a world where the conversation is the interface and the personality is the new User Experience.
One of the first cases where the Robotics for Customers approach has faced Chatbots has been in the automotive industry, where online assistants have been conceived for product presentation and catalogue configuration.