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Conversational Artificial Intelligence (AI), often referred to as a cross between Natural Language Processing (NLP) and Natural Language Understanding (NLU), is an algorithm-based intelligence that helps computers listen, process, understand and understand human language. With COVID-19 accelerating the momentum of digital transformation, organizations have increasingly taken new ways to meet customer expectations for timely resolution of queries. An important part of the customer experience process, conversation AI, quickly comes to the fore.
A Living Person survey shows that 91% of customers prefer companies that offer them the choice between calling or texting. Chatbots are an effective way for businesses to meet this demand. As customers increasingly expect round-the-clock availability from businesses, chatbots have become an effective way to make this possible. Chatbots are cost effective, efficient and able to routinely handle human queries, making it possible to reserve difficult queries to human agents.
With the influx of AI-powered chatbots also comes a need for sophistication, as well as the need for chatbots to understand questions and produce the right answers to help customers get the best experience. This is especially relevant for the new metaverse space, as companies seek to improve their presence and user experiences in a virtual world.
Kore.ai, a Florida-based company that focuses on providing companies with AI-powered virtual assistants, wants to bring conversational intelligence into the meta-verse. Raj Koneru, CEO of Kore.ai, told VentureBeat in an exclusive interview that conversational AI is the foundation of the meta-verse.
The advent of conversational AI
More and more companies have taken up the use of conversational AI over the past few years. Open source AI language models have now helped developers and companies in the conversation AI field to build better chatbots, speed up the customer experience and also improve the employee experience.
Conversational AI combines the practicality of AI to create a human-like interaction between the human asking the questions and the answering machine of the machine. Chatbots powered by conversation AI can recognize human speech and text. Conversation also takes place with an understanding of the intention, allowing for more precise answers.
As voice and conversation AI supports an increasing number of customer interactions, it also becomes more important for bots to leverage historical data by linking voice call data to message call data. Conversational AI helps make this possible by helping machines understand the human voice they are listening to, understand biases, and process the answers people seek.
Shorten shipping and deployment without sacrificing ease of use
Businesses need their chatbots built with conversation AI, Koneru said. The problem, however, is that building such solutions from scratch requires a long process that includes writing a lot of code. This can hurt the customer experience as chatbots will continue to be less effective when creating conversation AI. The long wait is often the result of problems such as sophisticated levels, language and geographic support. Account should also be taken of the time required to train AI and ensure that it is ready for market adaptation.
To shorten the wait, many companies turn to companies like Kore.ai, which offer a code-free automation platform that meets the AI needs of companies looking to improve the customer experience and interaction with their products.
Gartner Magic Quadrant for Enterprise Conversational AI Platforms 2022 shows Kore.ai as a leader in the field of conversation AI and shows the company’s upward path in the industry. Other companies on the list include Amelia, Cognigy, Omilia, IBM and OneReach.ai.
Koneru said that Kore.ai uses a combination of NLU approaches – including core meaning (semantic understanding), machine learning and knowledge graph – to identify user intent with a higher degree of accuracy, high and perform complex transactions. He said Kore.ai can achieve a high level of accuracy by following specific methods, including:
- Basic meaning: Analyzes the structure of a user’s utterance to identify words by meaning, position, inflection, capital letters, plurality, and other factors.
- machine learning: uses state-of-the-art algorithms and models to predict intent.
- Knowledge graph: Provides the intelligence needed to represent the importance of key domain terms and their relationships to identify user intentions.
- Ranking and resolution engine: determines the winning intention based on the scores provided by the three engines.
Gartner predicts that 25% of people will spend at least one hour a day in Metaverse by 2026, prompting companies to participate in the race to claim their place in Metaverse. Companies prepare customer contact points and proactively map user experiences.
According to Koneru, people will have conversations with avatars, essentially chatbots, in the metaverse. It is therefore important to create avatars that can understand the dynamics of human conversation, process it and give accurate results, even with all the human nuances that can interfere. This is where conversation AI comes in.
The use of conversational AI to enhance virtual experiences in Metaverse promises much, as Koneru noted, “Metaverse is ripe for many use cases that traditional companies can benefit from.”
“There must be good reasons in the business processes that lend themselves to a physical presence that prevents them from doing so digitally. The same is true of the post office and many educational offerings. If you think about telehealth, it could potentially be one of the strongest uses to step into the metaverse and come across a virtual representation of your doctor that can control your vital signs, ”he said.
According to Koneru, Kore.ai’s efforts to enhance the Metaverse world with conversational AI will make it the first conversational AI company to focus on Metaverse businesses while meeting the needs of everyday businesses. However, G2’s review shows that Kore.ai has competition in Intercom, Zendesk Support Suite, Drift, Birdeye and others.
Kore.ai has raised $ 106 million in equity financing over the past eight years and currently serves more than 200 Fortune 2000 companies.
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