Key Conversational AI Component Technologies

Natural Language Processing(NLP)

the ability to read or parse human language text

Intent Recognition

the ability to understand what the user is requesting, even if phrased unexpectedly, and vital for good user experiences.

Machine Learning

The ability to learn how better to respond to users by analysing human agent responses


the ability to pull data from web services or databases using Application Program Interfaces(APIs), run conditions and inform the Dialog Manager.

Voice Optimised Responses

The ability to engage in conversation in a humanlike manner and show emotions to deliver an optimised experience.

Dynamic Text to Speech

converting written text to natural-sounding speech, supporting diverse languages, voices and accents, and allowing emphasis of capital letters and tonal inflection.

Entity Recognition

understanding that some data refers to informative abstract categories, or entities. For example that “October 4th’ = Date. A key requirement for more complex commands and analysis.

Contextual Awareness

The ability to follow conversation history, translate, recall and memorise information over conversations. Essential for natural, humanlike conversations.

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Omni-channel experience

A single consistent experience, integrating channels with each other so customers receive consistent support.


enabling customers to complete the task they need whenever and wherever they want in a cost-efficient manner.

Real-time personalisation

personalised products, service, offers, and content in real- time based on the customer context and needs to offer a truly differentiated experience .

Sentiment analysis

identifying, quantifying and extracting emotions across channels to understand the social sentiment of their brand, product or service.

Conversational interfaces

enabling users to have conversations with machines that feel natural, by speech or text.

Predictive sales leads

scoring users’ likelihood of converting based on internal and external data, enabling sales to prioritise leads.

Automatic knowledge base & content creation

Identifying the most relevant data insights to automatically create custom content for each user and provide service recommendations to employees.

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