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Ami provides a conversational user experience.
Ami's conversational AI brain was developed by our team with attaining goals as its primary success measure.
Ami's Conversational AI uses the sum of Ami's learnings to automate customer service tasks and provide a personalised experience for customers.
Ami was built to control and learn from multiple layers. The layers prioritise the importance and relevance of Ami’s answers.
Additional layers enable Ami's neural network to leverage and orchestrate even more layers and data sources. Ami uses the layers and data sources to coordinate, communicate, interrogate, decide, learn, and validate.
Ami benefits from high-throughput data access.
Ami constantly reads all the available data in real time, ensuring that it is always accessible and useful for making decisions.
The algorithm is predicated on maximising effectiveness and achieving goals using multiple layers.
Ami can read websites, live data, data bases, APIs and more.
Ami's machine learning algorithms analyse user behaviour and preferences. Performance data enriches the data available to Ami.
Ami has the ability to identify relationships between facts, beliefs, concepts, and other pieces of information, and to learn from those connections.
Ami's understanding is geared around verbal reasoning. This involves formulating effective questions and using machine learning to determine if the question has been effective - learning to a goal.
Ami's automated conversational utterances can be delivered in text-based conversations on websites, Facebook Messenger, WhatsApp and more.
Ami Voice delivers Ami's fluid, automated conversations on telephones, VOIP platforms and much more.
Machine learning algorithms analyse user behaviour, preferences, and performance data to generate the most effective utterance possible for clients' customers.
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