Conversational AI applications enable seamless and automated communications between brands and customers. Using Machine Learning (ML) algorithms and Natural Language Processing (NLP) capabilities, these tools can:

• Recognise speech and text inputs from human users
• Decipher language syntax, nuances and context
• Understand user intent
• Translate their meanings
• Engage in multi-turn dialogues by generating natural language responses
• Answer queries, address concerns and resolve issues in near-human, natural language

With conversational AI, companies can automate mundane tasks for marketing, promotions, and several use cases. The technology improves the productivity of human support agents to focus on more high-value and meaningful activities.

By combining conversational AI with human support, organisations can redefine customer experiences. A conversational AI platform like Gupshup provides bot-builder tools, pre-built templates and conversation flow designers so any organisation can easily incorporate conversational AI into their customer interaction workflows.

Organisations can choose from many types of conversational AI tools. Chatbots are the most popular application of conversational AI. One can implement conversational AI chatbots on the company’s website or other channels like Facebook Messenger, WhatsApp, Slack, etc., to automate part of their support, marketing or commerce workflows, and interact with customers in personalised, contextual ways. Other applications of conversational AI include mobile assistants, voice assistants, and Interactive Voice Response (IVR) systems.

Conversational AI platforms like Gupshup are so versatile that they can be adapted to create conversational AI applications for any industry, including banking and finance, insurance, retail and eCommerce, F&B, travel and hospitality, as well as government, telecom, IoT, automotive, energy, and media and entertainment.

Conversational AI translates language so a machine (e.g., a chatbot or voice assistant) can understand users and respond to them in a human-like manner. The tool or application relies on:

• Automatic Speech Recognition (ASR)
• Natural Language Processing (NLP) or Natural Language Understanding (NLU)
• Text-to-Speech (TTS) with voice synthesis

Plus, one can fine-tune its AI language model by training it on domain-specific vocabulary. The enterprises can use pre-built conversational dialogue scripts and customise them w.r.t personality, tone, etc.

A conversational AI engine forms a core part of the Gupshup Conversational Messaging Platform (CMP). The CMP includes DIY tools and a workbench (no-code, low-code, yo-code), plus DIFM AI models and pre-built, pre-tested templates that work in plug-n-play mode. The engine drives all conversational and messaging experiences and plays a role on the client-side in B2C apps like GIP Messenger.

It enables the creation of intelligent bots which can work with other bots to compose, collaborate, delegate, transact, negotiate, self-upgrade and route. The engine allows the organisations to set up pre-built conversational experiences, build advanced, and enterprise-grade bots to drive automated, meaningful customer communications at scale.