12 top conversational AI platforms for 2024

The evolution of conversational AI from a novelty to an indispensable tool in daily life has been propelled by innovations like ChatGPT. According to Statista, the chatbot market is projected to reach $1.25 billion by 2025, underlining its growing significance. With capabilities spanning content generation, customer inquiries handling, and email composition, AI chatbots have swiftly gained popularity across domains.

A study by Search Engine Journal revealed that 40% of users are interested in chatbot experiences from brands. Conversational AI chatbots offer advanced solutions for customer service and virtual assistance. Understanding the workings of conversational AI is essential to fully harness the potential of these platforms. This article explores the nuances of conversational AI, comparing it with traditional chatbots, detailing its functioning and benefits, and guides businesses through the top 12 platforms of 2024, along with criteria for choosing the right one.

What is conversational AI?

Conversational AI refers to the use of artificial intelligence to enable computers to simulate real-time human conversation, understanding natural language and responding intelligently. It powers applications like virtual assistants and chatbots, providing users with automated, yet seemingly human-like, interactions. These technologies see diverse applications across industries, from customer service bots in retail to streamlining reservation systems in travel, and even providing round-the-clock support in technology services.

Conversational AI vs chatbots

Chatbots, as a subset of conversational AI, offer basic, scripted interactions, while more sophisticated conversational AI systems provide adaptive, context-aware conversations that learn over time. Here are the key differences between the functionality of each solution:

• Chatbots rely on predefined rules or responses; conversational AI employs advanced algorithms for understanding user intent and context.
• Chatbot personalization is often simplistic and based on user profiles; conversational AI adapts responses based on user behavior for sophisticated personalization.
• Chatbots are suitable for basic tasks like FAQs; conversational AI excels in complex scenarios like customer support and sales.
• Chatbots primarily engage in text-based interactions; conversational AI interprets voice, text, and image inputs.
• Chatbots sometimes operate without machine learning; conversational AI relies on advanced machine learning algorithms.
• Conversational AI enables natural conversations via speech recognition and cognitive response systems, integrating seamlessly across various communication channels.

How does a conversational AI platform work?

The functioning of a conversational AI involves several key components driven by machine learning. Initially, these platforms translate specific inputs into corresponding outputs. With the aid of machine learning, they can handle a broader spectrum of inquiries. Moreover, they factor in context—such as the ongoing conversation—to discern user intent and craft appropriate responses.

• Natural Language Processing (NLP) serves as the backbone of these systems. It dissects, comprehends, and acts upon user inputs. NLP includes dialogue control and task prediction, facilitating seamless interaction.
• Dialogue control modules ensure the natural progression of conversations by adapting pragmatically to user inputs. Meanwhile, task prediction mechanisms analyze speech patterns to anticipate user intentions, improving the platform’s responsiveness.
• Natural language understanding, a subset of NLP, delves deeper into textual and verbal structures, enabling precise interpretation of user intent. It accommodates human errors such as spelling and grammar mistakes and mispronunciations, ensuring accurate comprehension.
• Natural Language Generation (NLG) synthesizes coherent and persuasive responses, making interactions feel fluid. Top NLG vendors continually refine this technology to improve user experience, making conversations sound less robotic and more human.

Advantages of using conversational AI

According to Salesforce’s The State of Service Research report, 77% of agents believe that automation tools will enable them to finish more complicated tasks. This figure indicates the place of conversational AI in customer service, along with other verticals such as AI in web development, AI in product management, and so on, upending traditional operational approaches.

Here are some of the key advantages of leveraging conversational AI software in your business operations:

• Improved operational efficiency. The availability of AI-driven chatbots for customer support around the clock contributes to operational efficiency. According to a Deloitte report, 81% of contact center executives are investing in agent-enabling AI to streamline operations. Conversational AI streamlines tasks, allowing employees to prioritize personalized customer interactions.
• Cost savings. Businesses can easily scale their customer support operations with conversational AI. Chatbots can handle a surge in inquiries without needing to hire additional agents, making them ideal for seasonal businesses or those with fluctuating customer traffic.
• Efficient data collection. By transcribing and analyzing recorded interactions, businesses can extract valuable insights into customer preferences and trends, refining their sales and marketing strategies accordingly.
• Personalized customer support. Through analysis of various factors such as location, preferences, and account history, AI can generate tailored recommendations, ensuring a personalized customer experience.
• Improved customer experience. The omnichannel capabilities of conversational AI provide improved accessibility, allowing customers to engage seamlessly through their preferred communication channels, whether it be calls, text messages, social media, or chat.

Conversational AI use cases

Conversational AI is rapidly transforming the way businesses interact with customers and employees. Cutting-edge conversational AI platforms now feature integrated Generative AI, also known as GenAI, enhancing customer experiences and conversation quality through markedly improved relevance and response accuracy.

Here’s a glimpse into some of the most impactful use cases for conversational AI:

• Guiding new user onboarding. Conversational AI can walk users through product features, answer frequently asked questions, and personalize the experience based on their needs.
• Resolving issues in real-time. Conversational AI chatbots can troubleshoot common problems, answer basic inquiries, and escalate complex matters to human agents, providing immediate support, and significantly reducing resolution times.
• Empowering self-service solutions. Offers customers and employees 24/7 access to self-service options, guiding users through knowledge bases, FAQs, and tutorials, empowering them to find solutions independently.
• Facilitating training. Conversational AI chatbots can present training materials, answer questions, and simulate real-world scenarios, improving knowledge retention.
• Soliciting and processing employee feedback. Facilitates anonymous employee surveys, analyzing sentiment and identifying areas for improvement in company culture or work processes.
• Enabling virtual assistant capabilities. Conversational AI can automate tasks like scheduling meetings, booking travel, or summarizing key information from documents, improving productivity and streamlining workflows.
• Conducting automated market research. Gain real-time customer insights by conducting surveys and polls at scale, gathering valuable customer feedback, and identifying emerging trends to inform product development and marketing strategies.
• Driving automated sales processes. Conversational AI chatbots can answer sales inquiries, schedule demos, and score leads, freeing up sales teams to focus on closing deals.

How to choose the right conversational AI platform for your business

While conversational AI offers a powerful tool for businesses to improve customer experience and streamline operations, selecting the right platform can feel overwhelming. This section explores key factors to consider when choosing a conversational AI platform for your business in 2024:

1. Technical considerations and compatibility

• Infrastructure: Consider your existing technology stack. Does the platform integrate seamlessly with your CRM, website, and data analytics, or other crucial business tools?
• Security: Ensure the platform prioritizes data security and adheres to relevant industry compliance standards.
• Scalability: Think about future growth. Can the platform handle increasing customer interactions without compromising performance?

2. Multi-channel support evaluation

• Channel availability: Where do your customers interact with you most? Does the platform support your preferred channels (website chat, social media messaging, voice assistants, etc.)?
• Omnichannel experience: In today’s omnichannel landscape, customers expect a consistent experience across channels. Does the platform enable seamless handoff between chatbot and human agents for complex inquiries?

3. Customization and adaptability assessment

• Branded interactions: Can you tailor the chatbot’s personality and tone to align with your brand voice?
• Conversation design flexibility: Does the platform allow you to design multi-layered conversations with branching logic and personalized responses?
• Self-learning capabilities: Can the AI learn from interactions and improve its responses over time, reducing the need for manual intervention?

4. Training resources and support availability

• Ease of use: Consider the platform’s user interface and learning curve. Does it offer a no-code interface or require coding expertise for development?
• Training documentation: Does the platform provide comprehensive documentation and tutorials to get you started?
• Ongoing support: What level of ongoing support does the vendor offer? Is there readily available technical assistance if needed?

12 top conversational AI platforms for 2024

Businesses aiming to harness the advantages of conversational AI must make a crucial decision in selecting the right platform. To facilitate this process, we’ve curated a list of the top 12 conversational AI platforms and key features:

1. IBM Watsonx Assistant

IBM Watsonx Assistant is designed to elevate user experiences while streamlining traditional assistance processes. It delivers automated self-service support across diverse communication channels. This application empowers users to develop AI chatbots capable of understanding human interactions and adapting to specific business requirements.

Key features:

• Advanced AI chatbot technology for enhanced customer experience by understanding and responding to human conversations intelligently.
• Ensures robust data privacy and security measures, safeguarding sensitive information and customer trust.
• Facilitates customization of the AI voice chatbot’s tone, ensuring a clear and friendly interaction interface.

2. Amazon Lex

Amazon Lex offers a comprehensive service tailored for constructing conversational interfaces using both voice and text inputs. Leveraging automatic speech recognition, it transcribes spoken language into text and employs text-to-speech functionality to render text into audible speech. With Amazon Lex, users can develop virtual agents and voice assistants, supported by a range of components aimed at creating intelligent conversational AI solutions for businesses.

Key features:

• Empower AI to discern intent, automate routine tasks, and maintain contextual understanding.
• Simplify the creation of omnichannel conversational AI through intuitive design tools.
• Seamlessly integrate with various AWS services to execute business logic, retrieve data, and more.

3. Yellow.ai

Yellow.ai offers a multi-LLM architecture that ensures exceptional performance. Continuously refined through billions of conversations, it excels in scalability, speed, and accuracy. This platform effectively slashes operating costs by automating conversations across various channels, including email, text, and voice. Yellow.ai supports over 135 languages and facilitates interactions across more than 35 channels.

Key features:

• Streamlined agent design and deployment without prior AI knowledge, ensuring rapid implementation.
• Supports multiple concurrent call capacities, enhancing efficiency and scalability.
• Harnesses generative AI capabilities to empower any virtual assistant.

4. Cognigy.AI

Cognigy.AI is an advanced conversational platform, that facilitates contact center automation for both employees and customers. It offers comprehensive customer service solutions, including agents, conversational IVR, and assistants, alongside intelligent self-service options. The platform enables integration with existing backend systems, allowing users to design bespoke conversational flows and customize virtual assistants or chatbots to suit their unique business requirements. Through Cognigy.AI, organizations can forge meaningful connections and nurture customer loyalty by delivering personalized experiences.

Key features:

• Creation of AI agents tailored to business needs.
• Seamless integration with existing systems.
• Simplified development of AI agents for customer and agent support.
• Real-time AI coaching for workforce empowerment.

5. Aisera

Aisera offers AI-driven solutions tailored for proactive, personalized, and predictive experiences, supporting HR, IT, sales, and customer service operations. By harnessing user and service behavioral intelligence, Aisera streamlines tasks, actions, and business processes. Noteworthy enterprise clients including Zoom, Workday, Amgen, McAfee, Autodesk, Chegg, Dave.com, and 8x8 have embraced Aisera’s products.

Key features:

• Focuses on enterprise-grade AI, emphasizing security and scalability.
• Integrates with various business systems for a holistic customer view.
• Leverages GPT-3 for powerful natural language processing.

6. Amelia

Amelia specializes in crafting intelligent virtual assistants (IVAs) adept at understanding and responding to human language. Utilizing proprietary NLP technology and Generative AI models, Amelia orchestrates seamless, natural conversations. Organizations benefit from exceptional customer and employee experiences with IVAs accessible 24/7 across channels, in 100+ languages. IVAs excel in answering queries, guiding complex interactions, and automating business processes.

Key features:

• Known for its advanced natural language understanding and ability to handle complex conversations.
• Integrates with CRMs and other enterprise applications for a unified experience.
• Offers pre-built industry-specific solutions to get you started quickly.

7. Boost.ai

Boost.ai, a conversational artificial intelligence platform, offers both cloud-based and on-premise solutions tailored for diverse industries like banking, telecom, retail, and more. Leveraging self-learning AI, deep learning, natural language processing (NLP), and automatic semantic understanding (ASU) technology, it interprets and responds to queries efficiently. Features include a centralized information repository, authentication management, pre-defined templates, language detection, conversational IVR, and an AI-enabled admin panel facilitating natural interaction development in a user-friendly, no-code environment. Boost.ai enables managers to glean insights from conversational data, quality ratings, and other metrics through analytics and supports integration with various third-party applications.

Key features:

• Stands out for its omnichannel capabilities, supporting voice, chat, messaging apps, and more.
• Offers a user-friendly no-code interface for building chatbots.
• Provides tools for sentiment analysis and conversation insights.

8. Tars

Tars specializes in optimizing conversion funnels and automating customer service interactions through chatbots, with a primary focus on enhancing the customer experience. Utilizing a chatbot or conversational landing page, Tars engages visitors in automated chats providing relevant service or product information, preventing information overload. This strategy boosts lead generation effectiveness by increasing the likelihood of users sharing their contact information. Additionally, Tars offers an extensive library of chatbot templates catering to various industries and use cases.

Key features:

• Emphasizes flexibility and customization for building unique chatbots.
• Integrates with various development tools and platforms.
• Offers a modular architecture for tailoring functionalities.

9. Avaamo conversational AI platform

The Avaamo conversational AI platform specializes in delivering agency-grade chatbots and digital assistants, tailored for various industries including banking, insurance, and healthcare. It enables organizations to automate customer interactions and streamline internal processes. Leveraging natural language processing and machine learning, Avaamo’s platform synthesizes and responds to consumer queries, providing personalized conversational experiences. With a focus on enterprise use cases, Avaamo aims to improve customer service, employee productivity, and operational efficiency through its AI-powered conversational interfaces.

Key features:

• Rapid bot deployment process, even for enterprise-grade solutions.
• Speech synthesis for enhanced conversation and problem-solving.
• Enterprise-grade security and compliance.
• Seamless transition from voice to chat to text for continuous conversation engagement.

10. Oracle Digital Assistant

Oracle Digital Assistant offers a comprehensive AI platform that integrates chat, text, and voice interfaces to create conversational experiences for business applications. Businesses can use this platform to develop chatbots that understand user intents, hold natural language conversations, and provide relevant responses. This enables users to interact with the AI chatbots on the business’s own website or within applications they use, such as Microsoft Teams or Facebook Messenger.

Key features

• Voice command functionality for effortless communication with business applications.
• Accurate intent and context derivation in common conversations.
• Built-in analytics identifying conversational bottlenecks and usage patterns for improved performance analysis.

11. Microsoft bot framework

The Microsoft Bot Framework facilitates the development of conversational AI chatbots capable of interacting with users across various channels such as websites, Slack, and Facebook. It supports both no-code and code-first approaches, offering a language component to create natural language experiences. Additionally, the framework provides speech components enabling bots to respond naturally in a branded voice, translate messages, recognize commands, and identify individual speakers.

Key features:

• Build, test, and connect bots using open-source SDK tools.
• Secure, scalable, and globally accessible solutions, integrating with existing IT infrastructures.
• Develop AI experiences that seamlessly align with and enhance your brand identity.

12. Google Dialogflow

Google Dialogflow is a natural language understanding platform, that facilitates the integration of conversational user interfaces across multiple platforms. Powered by machine learning, Dialogflow enables seamless comprehension and response to user input, supporting both text and voice interactions. With integrations spanning Google Assistant, Facebook Messenger, and Slack, Dialogflow empowers developers to create highly customizable conversational experiences.

Key features:

• Popular choice for its ease of use and tight integration with Google Cloud Platform.
• Supports a variety of conversation designs, including text and voice.
• Offers pre-built agents and rich integrations with other Google products.

FAQs:

What is conversational AI and how does it differ from regular chatbots?

Conversational AI uses artificial intelligence to enable computers to simulate real-time human conversation, understanding natural language and responding intelligently using NLP algorithms. Unlike traditional chatbots which operate on predefined scripts and are primarily text-based, conversational AI supports voice, text, and image inputs, facilitating more dynamic interactions with context awareness.

What key factors should businesses consider when choosing a conversational AI platform?

Businesses should evaluate infrastructure compatibility with existing CRM and business tools, security measures and industry compliance standards, and scalability to handle increasing customer interactions without compromising performance. Channel availability is also crucial the platform should support your preferred channels like website chat, social media messaging, or voice assistants.

How does Natural Language Processing work in conversational AI platforms?

NLP serves as the backbone of conversational AI systems, dissecting, comprehending, and acting upon user inputs through dialogue control and task prediction mechanisms. Dialogue control modules ensure natural conversation progression by adapting pragmatically to user inputs, while task prediction mechanisms analyze speech patterns to anticipate user intentions.

What are the main business benefits of implementing conversational AI?

Conversational AI enables 24/7 customer support, guiding users through product features and answering frequently asked questions while personalizing experiences based on user needs. It empowers self-service solutions by providing customers and employees access to knowledge bases, FAQs, and tutorials, significantly reducing resolution times and improving customer satisfaction.

Accelerate your AI projects with DigitalOcean Gradient GPU Droplets

Accelerate your AI/ML, deep learning, high-performance computing, and data analytics tasks with DigitalOcean Gradient GPU Droplets. Scale on demand, manage costs, and deliver actionable insights with ease. Zero to GPU in just 2 clicks with simple, powerful virtual machines designed for developers, startups, and innovators who need high-performance computing without complexity.

Key features:

• Powered by NVIDIA H100, H200, RTX 6000 Ada, L40S, and AMD MI300X GPUs

• Save up to 75% vs. hyperscalers for the same on-demand GPUs

• Flexible configurations from single-GPU to 8-GPU setups

• Pre-installed Python and Deep Learning software packages

• High-performance local boot and scratch disks included

• HIPAA-eligible and SOC 2 compliant with enterprise-grade SLAs

Sign up today and unlock the possibilities of DigitalOcean Gradient GPU Droplets. For custom solutions, larger GPU allocations, or reserved instances, contact our sales team to learn how DigitalOcean can power your most demanding AI/ML workloads.