Natural language processing (NLP) and machine learning (ML) are used in conversational AI platforms to enable natural and interesting interactions between humans and robots. Chatbots, virtual assistants, voice assistants, and other applications that can comprehend and respond to human commands and questions can be developed using conversational AI systems.
We will examine the top 10 conversational AI platforms of 2023 in this post based on their acceptance, usefulness, and innovation. These are the platforms:
Google Cloud Conversational AI
This is a complete set of goods and services that aid in the development, deployment, and management of conversational AI applications for organizations and developers. It includes Conversational AI on Gen App Builder, a tool for building generative AI-powered chatbots and virtual agents, Dialogflow CX, a developer platform for creating advanced conversational agents, Contact Centre AI, a solution for integrating conversational AI into customer service, and Speech-to-Text and Text-to-Speech APIs for converting speech and text inputs and outputs.
Watson Assistant by IBM
Without writing any code, users may construct conversational AI applications using this cloud-based platform. It uses machine learning (ML) and natural language understanding (NLU) to analyze and produce responses. Additionally, it provides pre-built content and channel and platform connectors. The service IBM Watson Discovery, which enables users to find and analyze data from diverse sources, is also available to users.
Amazon Lex
With the help of this service, users can create speech and text-based conversational interfaces. It makes use of the same technologies as the well-known voice assistant Amazon Alexa. To process user inputs and intentions, it offers automatic voice recognition (ASR) and natural language understanding (NLU). Additionally, it connects with the natural language processing (NLP) service Amazon Comprehend.
Microsoft Bot Framework
Users may create, test, launch, and manage conversational AI apps across many channels and devices with the aid of this framework. It supports a wide range of programming languages and frameworks, including C#, Python, JavaScript, and NET. Additionally, it connects with Microsoft Azure Cognitive Services, a set of APIs that offer artificial intelligence (AI) features like speech recognition, natural language processing, computer vision, and more.
Rasa
With the help of this Python-based open-source platform, users can create unique conversational AI apps. To handle complex discussions, it employs dialogue management (DM) and natural language understanding (NLU). Additionally, it offers contextual assistants, which may keep track of user objectives and recall prior encounters.
Nuance
Solutions for conversational AI are offered on this platform for many sectors and use cases. It provides items like Nuance Dragon, a product for speech recognition and transcription, Nuance Loop, a product for personalized customer engagement, Nuance Gatekeeper, a solution for biometric authentication, and Nuance Mix, a tool for building voice and chat applications.
SAP Conversational AI
Using machine learning (ML) and natural language processing (NLP), this platform enables users to create intelligent chatbots. It provides analytics, discourse management, sentiment analysis, entity extraction, and intent detection. Additionally, it integrates with several SAP services and products, including SAP Cloud Platform, SAP S/4HANA, SAP C/4HANA, and others.
Oracle Digital Assistant
With the help of this platform, users can build digital assistants that can communicate with people orally or textually. To comprehend user inputs and provide responses, it makes use of machine learning (ML) and natural language understanding (NLU). Additionally, it supports chatbots with a variety of talents, including those that can perform various tasks and domains.
Kore.ai
This platform offers complete conversational AI solutions for businesses. In addition to natural language processing (NLP), it provides analytics, security, compliance, dialogue management, knowledge management, sentiment analysis, speech recognition, text-to-speech synthesis, and analytics. It also supports a variety of channels platforms and system connections.
Haptik
This platform enables customers to create conversational AI applications for many different use cases, including appointment scheduling, lead generating, feedback gathering, and meal ordering, among others. To comprehend user inputs and provide responses, it makes use of machine learning (ML) and natural language processing (NLP). Additionally, it provides analytics tools, widgets, and pre-built templates.
