Conversational AI is key to the delivery of the next wave of customer and employee experiences(CX) . Advances in automation, artificial intelligence (AI) and natural language processing (NLP) now make it possible to design cost-efficient digital experiences, in which customer conversations with organisations increasingly resemble conversations with employees in-person. Conversational AI can be defined as a programmatic and intelligent way of offering a conversational experience that mimics conversations with real people, using digital and telecommunications technologies. Avenir Digital's Conversational AI products are powered by our own powerful and innovative CX platform, MiSHI.
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
Fulfilment
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.
Avenir Conversational AI Products, powered by MiSHi
Omni-channel experience
A single consistent experience, integrating channels with each other so customers receive consistent support.
Self-service
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.
