Artificial Intelligence You Can Talk To
Artificial Intelligence

Artificial Intelligence You Can Talk To

Mandi D 28 September 2023
Table of contents

In the rapidly evolving world of artificial intelligence (AI), one area that has seen significant growth and innovation is that of conversational AI platforms. These are sophisticated systems designed to engage in human-like dialogue, breaking down the barriers between human and machine communication.

These platforms have the capability to not only understand and respond to human speech but also learn from each interaction, allowing them to continually refine and improve their responses. The result is a communication tool that can provide personalized and efficient communication experiences, redefining the way businesses interact with their customers.

These conversational AI platforms leverage a combination of advanced technologies, including natural language processing, machine learning, and a range of intricate algorithms. Natural language processing enables these systems to understand and interpret human language as it is spoken or written, while machine learning algorithms allow the system to learn from each interaction, enhancing its future responses. This powerful combination of technologies brings us one step closer to a world where machine communication mirrors human conversation.

In the following article, we’ll take a deep dive into the world of conversational AI platforms. We’ll delve into a range of platforms, exploring their key features, and discussing their strengths and limitations. We’ll also consider the pricing structures of these platforms, where this information is available, to give you an idea of the investment required to implement these innovative solutions.

Whether you’re a business owner seeking to enhance customer communication or a tech enthusiast keen to understand the latest developments in AI, this article aims to provide a comprehensive overview of the current conversational AI landscape.

IBM Watson Assistant

IBM’s Watson Assistant is an artificial intelligence-powered conversational platform created by IBM that allows companies to automate customer service and other conversational interactions. The Watson Assistant service uses natural language processing and machine learning to understand what a customer is asking and provide an appropriate response by accessing the company’s knowledge base.

Some key capabilities of Watson Assistant include:

  • Natural Language Processing – Watson uses advanced NLP algorithms to analyze text and understand the intent behind a customer’s question or request. It can comprehend complex sentences, interpret slang and colloquialisms, and handle spelling mistakes.
  • Integrations – Watson Assistant can integrate with back-end systems like CRM platforms, ERP tools, databases, and internal company resources to retrieve relevant information to answer questions. Popular integrations include Salesforce, ServiceNow, and APIs.
  • Dialog Flow – The dialog flow enables creating guided conversations with branches, slots, and conditional logic to handle diverse customer needs and complex queries. It’s configurable through a graphical dialog editor.
  • Customizable Responses – Companies can customize responses for Watson to align with brand voice and tone. Responses can include text, images, videos, buttons, and more.
  • Self-Learning – Watson Assistant continuously improves its language understanding and response accuracy through machine learning. As it interacts with more customers, its natural language processing keeps getting better.
  • Analytics – Usage analytics give insights into how customers are interacting with the assistant. Companies can identify patterns, monitor performance, and optimize the assistant.
  • Secure Cloud Platform – Watson Assistant is hosted on IBM Cloud which enables secure and scalable deployments. IBM manages all the infrastructure and Watson upgrades.

Overall, Watson Assistant allows brands to automate customer support and front-end conversations at scale. With its conversational AI capabilities, the platform can significantly reduce customer support costs while also providing a personalized and seamless experience.

Google Dialogflow

Google Dialogflow is a natural language understanding platform that allows developers to design and integrate conversational interfaces into applications and devices. The tool can understand text-based conversations, extract key information, and respond in natural language.

Some of the key capabilities of Dialogflow include:

  • Natural Language Processing – Dialogflow applies machine learning to understand natural language input like colloquialisms, questions, and contextual meaning. This enables it to decipher user intent and entities.
  • Prebuilt Agents – Dialogflow offers prebuilt agents for common conversational scenarios like booking appointments, customer support, etc. This provides a headstart for developers.
  • Integrations – Dialogflow integrates with popular communication platforms like Facebook Messenger, Slack, Google Assistant etc. It also works with cloud platforms like AWS, Google Cloud.
  • Dialogflow Actions – Developers can configure conversational flows using Dialogflow’s GUI console. These dialog flows are called actions. The tool provides branching logic, contextual follow-ups, slot filling and more to handle complex conversations.
  • Customizable Responses – Developers can customize text responses, include rich media like images/videos, incorporate SSML for speech, and more to shape unique conversation experiences.
  • Analytics – Usage analytics give visibility into how end-users are interacting with the bots and assistants built using Dialogflow. Developers can analyze metrics to improve conversations.
  • API.AI Integration – Dialogflow was formerly known as API.AI before being acquired by Google. Existing API.AI bots and integrations can still be migrated over.

Overall, Dialogflow simplifies the process of designing, prototyping and deploying human-like conversational interfaces across various platforms and devices. Its robust NLP and seamless integrations with popular channels make it a versatile tool for developers.

Kore.ai Experience Optimization (EO) Platform

The Kore.ai Experience Optimization Platform is an end-to-end solution for optimizing digital experiences and customer journeys powered by artificial intelligence. It aims to help companies deliver more personalized, efficient and satisfying interactions across web, mobile and voice/chat channels.

Some key capabilities include:

  • Intelligent Virtual Assistants – The platform provides conversational AI chatbots and voicebots to automate customer support and front-end interactions. These virtual assistants can understand natural language, handle multi-turn conversations and complete tasks.
  • Journey Analytics – In-depth analytics give visibility into how users navigate products and services. Companies can identify pain points and optimize journeys by adding guided tours, intuitive layouts, proactive assistance etc.
  • Behavioral Targeting – User behavior like clicks, searches, purchases etc. are analyzed by the AI to deliver hyper-personalized recommendations and tailored content to drive engagement.
  • Connected Devices Support – The EO platform can power AI assistants on smart displays, speakers, cars, wearables and other connected devices. It provides seamless hand-offs between channels.
  • Unified Insights – Interaction data is aggregated across virtual assistants, websites, mobile apps etc. to build unified customer profiles. This powers consistent experiences across channels.
  • Flexible Deployment – Kore.ai offers cloud-based deployments on Azure, AWS and Google Cloud as well as on-premise and hybrid deployment options.

Pricing for the Kore.ai EO platform is customized based on the scale, use cases and capabilities required by each enterprise customer. Companies need to contact Kore.ai sales for an accurate quote tailored to their needs.

Haptik

Haptik is a leading conversational AI platform that enables automation of customer interactions across various channels like messaging, voice and web. It uses artificial intelligence capabilities like natural language processing, machine learning and contextual awareness to deliver human-like conversational experiences.

Some of the key features of Haptik include:

  • Pre-built Industry Solutions – Haptik offers pre-configured solutions tailored for industries like banking, insurance, retail etc. These speed up deployment.
  • Multilingual Support – The platform can handle conversations in multiple Indian and global languages to serve a wide customer base.
  • Analytics Engine – Provides actionable insights based on every customer interaction, helping improve conversation performance.
  • Agent Handoff – Seamlessly connects customers to human agents when needed, maintaining context from the virtual assistant chat.
  • Robust Security – Encrypted data flow with ISO 27001 certification ensures secure customer information access and storage.
  • Easy Integration – Flexible APIs and out-of-the-box integrations with communication channels and third-party data sources.
  • Customizable Business Solutions – Haptik offers customized conversational AI development specific to a company’s needs across industries and use cases.

Haptik provides its platform on a software-as-a-service subscription model. Pricing varies based on number of users, conversations and platform capabilities. Businesses can contact Haptik directly for an accurate quote.

Amazon Lex

Amazon Lex is a robust conversational AI service provided by Amazon Web Services that makes it easy for developers to build chatbots, virtual assistants and other conversational applications.

Key features of Amazon Lex include:

  • Automatic Speech Recognition – Lex converts speech to text and natural language understanding. This enables building voice-enabled assistants.
  • Intent Identification – Identifies the intent behind user input text/voice to route conversations appropriately.
  • Multilingual – Supports multiple languages including English, Spanish, German, French and more.
  • Prebuilt Blueprints – Comes with blueprints for common chatbot use cases like ordering food or booking hotels to accelerate development.
  • Integration with Amazon Connect – Can be integrated with Amazon’s contact center solution for conversational IVRs and agent assistance.
  • Analytics – Provides conversation metrics and logs to identify usage patterns and optimize the experience.
  • Flexible Deployment – Can be deployed on AWS Lambda and integrated with popular apps or deployed on devices.
  • Security – Lex provides data encryption both in transit and at rest to secure sensitive customer data.

Amazon Lex pricing is based on the number of text/voice requests processed. It provides a free tier for trying out the service. Overall, Lex makes it easy to add sophisticated natural language conversational capabilities to applications.

Microsoft Azure Bot Service

Microsoft Azure Bot Service provides a comprehensive platform to build, deploy and manage intelligent bots. It allows developers to create conversational AI applications that interact naturally with users across a range of platforms including websites, apps, messaging platforms and more.

Key capabilities include:

  • Prebuilt templates – Comes with pre-built bot templates for common scenarios like Q&A, appointments, surveys etc to accelerate development.
  • NLP with LUIS – Azure Bot Service integrates with Language Understanding Intelligent Service (LUIS) to understand natural language and extract relevant information.
  • Seamless integrations – Easy to integrate bots with channels like Teams, Facebook Messenger, Slack, SMS and custom apps.
  • Bot Connector Service – The connector service helps scale bots to thousands of users and provides tools to build engaging conversation flows.
  • Analytics – Provides chat metrics like user messages, conversations, user retention etc to improve the bot experience.
  • Security – Azure secures bot data with encryption, role-based access and other security controls.
  • DevOps for bots – Provides continuous integration and deployment capabilities for bots via Azure DevOps.

Pricing depends on the Bot Service plan and usage. The free tier supports basic testing. The standard plan starts at $0.50 per 1,000 messages. More advanced enterprise bot deployments are also supported. Overall, Azure Bot Service simplifies the process of building and launching AI-powered conversational interfaces.

Emerging AI Platforms

Dialpad

Dialpad is an AI-powered cloud business phone and contact center solution. Key features include:

  • Voice intelligence – Real-time speech recognition and transcription using AI. Generates insights from customer calls.
  • Unified platform – Unifies voice, video, messaging channels for seamless omnichannel customer experiences.
  • Smart routing – Intelligently routes calls to the right agents or auto-attendants using natural language understanding.
  • Agent assist – Provides next-best information and suggestions to agents in real-time during calls.
  • Analytics – Offers advanced analytics on call metrics, agent performance, customer sentiment etc. to optimize operations.
  • Flexible deployment – Available as a cloud platform or can be deployed on-premise. Integrates with popular business apps.

Overall, Dialpad uses AI and natural language processing to make business communications and contact centers smarter and efficient.

Sparkcentral

Sparkcentral is an intelligent customer service automation platform tailored for enterprise scale. Key capabilities:

  • Omnichannel – Provides seamless conversations with customers across messaging, social media, email and voice/video channels.
  • Smart routing – Uses ML and configurable rules to route inquiries to the right agents or bots.
  • Auto-escalation – Escalates complex requests to appropriate staff based on language analysis.
  • Unified inbox – Agents get a unified inbox across channels for efficient management at scale.
  • Automation – Prebuilt automations based on common customer intents to accelerate response.
  • Analytics – Conversation analytics reveals customer sentiment, agent productivity metrics, and areas of improvement.
  • Integrations – Flexible integrations with leading CRM and contact center platforms.

Overall, Sparkcentral uses automation and AI to optimize large-scale customer service operations across channels.

Ideta

Ideta applies deep learning and NLP to automate business communications via AI assistants. Key features:

  • Omni-channel assistants – Human-like AI chatbot assistants deployed across web, app, messaging, email and voice channels.
  • Deep learning – Advanced neural networks understand complex language and user intents.
  • Contextual awareness – Maintains conversation context and user profile for personalized responses.
  • Self-learning – Continuously improves conversational abilities by learning from real interactions.
  • Connectors – Integrates with back-end systems like ERP, CRM to access enterprise data.
  • Analytics – Provides interactive dashboards to analyze assistant performance and usage.
  • Omnichannel – Unified experience across chat, voice and digital touchpoints.

By leveraging deep learning and NLP, Ideta enables hyper-automation of customer interactions resulting in enhanced experience and efficiencies.

Conclusion

Conversational AI platforms are dramatically altering our interactions with technology and businesses, serving as a transformative bridge between human language and digital data. These platforms harness the power of artificial intelligence to interpret and respond to human speech or text, fostering more natural and effective communication.

As a result, they are democratizing technology by making it more accessible and user-friendly, breaking down barriers that might have once made tech seem intimidating or inaccessible to certain user demographics.

Among the most prominent platforms in this rapidly evolving field are IBM Watson Assistant, Google Dialogflow, Kore.ai experience optimization (EO) platform, LivePerson Conversational Cloud, Oracle Digital Assistant, S.A.P conversational AI, Yellow.ai enterprise conversational AI & chatbot Platform, Amazon Lex, Microsoft Azure Bot Service, and Haptik. Each of these platforms provides a unique set of capabilities to meet various business needs, from customer service automation to personal assistant functionalities.

In addition to these, there are other platforms like Dialpad, Sparkcentral by Hootsuite, Ideta, Kasisto, ConvyAI, Avaamo, Clinc, Rasa, Replicant, ServisBOT, NTT Data’s Eva, AI Rudder, Nuance, and SurveySparrow that are making significant strides in the field.

These platforms offer unique features such as superior speech recognition, powerful automation, natural language interaction, comprehensive analytics, and more. These features enhance the user experience, streamline business processes, and in turn, lead to an increased return on investment.

Despite the remarkable progress so far, it’s essential to note that the conversational AI landscape is not static. It is a dynamic and continually evolving field driven by advancements in machine learning, natural language processing, and other related technologies.

As such, we can anticipate the emergence of even more innovative and sophisticated solutions in the years to come. These future developments may bring about novel ways of interaction, more advanced features, and possibly unforeseen applications of conversational AI.

Furthermore, as these technologies become more prevalent, it will be crucial to address potential challenges and ethical considerations, such as data privacy and the impact on employment. How we navigate these issues will play a significant role in the successful and responsible implementation of conversational AI in our everyday lives and business operations.

In conclusion, conversational AI platforms are not just transforming our interaction with technology and businesses but are also set to shape the future of digital communication. These platforms are making technology more accessible, intuitive, and responsive, ultimately leading to a more user-friendly digital landscape.

While the platforms listed above are leading the charge today, the continuous evolution of the AI landscape promises even more groundbreaking advancements in the years to come. As such, conversational AI platforms represent a thrilling frontier in the ongoing exploration of AI’s potential to enhance our lives and business operations.