50+ Chatbot Companies To Deploy Conversational AI in 2024: A Detailed Overview

ByPaul Christiano Last Update on

Hey there! Chatbots and conversational AI are changing the way many companies interact with their customers. Businesses across industries are using chatbots to automate routine conversations, provide 24/7 support, and deliver personalized recommendations.

But with so many platform options, it can be tricky to determine the best fit for your needs. This guide will walk you through the key things to evaluate when choosing a chatbot provider and profile over 50 top vendors to consider. Let‘s dive in!

Why Are Businesses Adopting Chatbots?

It‘s clear that chatbots are going mainstream. Gartner predicts that by 2025, 70% of white-collar workers will interact with conversational platforms on a daily basis. What‘s driving this surge in adoption?

Key Benefits

  • Improved Customer Experience – Chatbots provide quick, personalized and seamless engagements for today‘s on-demand consumers.
  • Operational Efficiency – Automating repetitive tasks like order status checks and FAQs frees staff to focus on higher value work.
  • Cost Savings – Chatbots scale easily to handle high volumes without additional hiring. They can reduce customer service costs by 30% or more.
  • Revenue Growth – Chatbots generate more sales by guiding shoppers, surfacing relevant products/services and enabling transactions.

The Numbers

  • The global chatbot market size is projected to grow from $2.6 billion in 2019 to $10.5 billion by 2026. (MarketsandMarkets)
  • 85% of interactions between a business and customer will be handled without human agents by 2022. (Gartner)
  • Chatbots can deliver ROI of up to 2000% in the first year alone. (IBM)

It‘s clear that chatbots are becoming a customer service and brand differentiator that companies cannot ignore. Now let‘s explore the leading platform options.

Chatbot Platform Comparison

There are two main types of conversational AI platforms:

1. Self-Service Developer Platforms

These provide the natural language processing (NLP) capabilities, tools and APIs for developers to build customized chatbots tailored to your needs.

Pros

  • Full control over implementation and customization
  • Tight integration with your own backend systems
  • Leverage powerful AI capabilities like contextual NLU

Cons

  • Requires developer resources and expertise
  • You manage ongoing maintenance and improvements
  • Limited prebuilt content and industry solutions

Best For

Companies with some developer capacity that want to create proprietary and extensively customized chatbots.

2. End-to-End Chatbot Platforms

These require minimal technical expertise and provide a complete managed solution including building, deploying and managing your chatbot.

Pros

  • Fast time-to-value with prebuilt solutions
  • Vendor manages updates and enhancements
  • Leverage vendor‘s deep experience across industries

Cons

  • Less flexibility and customization
  • Higher costs and vendor dependencies
  • Longer vendor contracts

Best For

Companies that want a turnkey chatbot solution without needing to build competencies in-house.

Now let‘s explore the leading options in each category.

Top Self-Service Chatbot Platforms

Here are 5 of the most popular developer platforms for building advanced, custom conversational AI chatbots:

Google Dialogflow

  • Leading natural language understanding platform for building chatbots, voice assistants
  • Strong NLU capabilities like context, intent recognition, entities
  • Prebuilt agents for common use cases
  • Integrates seamlessly with Google ecosystem and Assistant
  • Pricing: Free tier. Standard ($0.002 per request) to Enterprise pricing

IBM Watson Assistant

  • Build, deploy and manage conversational AI with IBM‘s enterprise-ready platform
  • Leverage machine learning and NLP for natural conversations
  • Extensive prebuilt industry and task-specific content
  • Pricing: Lite (free for 5 assistants), Standard ($0.0025 per message) to Enterprise plans

Microsoft Bot Framework

  • Comprehensive SDK and tools for building bot experiences across platforms
  • Strong capabilities for language understanding and dialog management
  • Integrates seamlessly with Azure and Microsoft ecosystem
  • Hundreds of samples and extensive documentation
  • Pricing: Free. Azure usage charges apply.

Amazon Lex

  • Managed service from AWS enables conversational interfaces for Alexa and chatbots
  • Build, test and deploy chatbots without managing infrastructure
  • Deep learning powers accurate speech recognition and language understanding
  • Pricing: Tiered pricing based on messages, audio minutes, languages

Rasa

  • Leading open source conversational AI framework
  • Modular architecture for context-driven dialog management
  • Active community provides support and shares best practices
  • On-premise deployment provides data privacy and control
  • Pricing: Open source free. Commercial licenses from $149/mo

Top End-to-End Chatbot Providers

Here are the leading managed service providers for deploying chatbots quickly without needing to build expertise in-house:

Haptik

  • One of the world‘s largest conversational AI platforms
  • 700M+ interactions via chatbots, voice assistants, live chat
  • Prebuilt solutions and expertise across multiple industries
  • Customers include Disney, Tata, HP, Unilever, Zurich Insurance
  • Pricing: Message-based tiered pricing. Enterprise packages.

Nuance

  • Pioneer in conversational AI and ambient intelligence
  • Specialized virtual assistants for healthcare, banking, telecom
  • Powers intelligent self-service solutions for Fortune 2500
  • Leading embedded automotive assistant technology
  • Pricing: Contact for quote based on use case

Creative Virtual

  • Cloud-based conversational AI to automate engagements
  • Prebuilt solutions for banking, aviation, healthcare and more
  • Chatbots handle 50M+ conversations annually
  • Flexible self-service bot builder to train AI models
  • Pricing: Subscription plans based on messages, hours, use case

Inbenta

  • AI-powered self-service chatbots for customer support
  • Natural language search and NLU understands 12 languages
  • Key customers include Fiserv, eBay, Walmart, Cisco
  • Chatbot builder and analytics dashboard
  • Pricing: Custom quote based on monthly active users

Personetics

  • Conversational AI for digital banking and commerce
  • Financial bots guide customers and handle transactions
  • Deployed by 6 of top 12 US banks and large retailers
  • Securely integrates with existing banking and CRM systems
  • Pricing: Contact sales for customized quote

In addition to chatbot pure-plays, the major customer engagement platforms like Salesforce, Zendesk and Intercom now offer conversational AI capabilities. Leading IT consultancies like Deloitte and Accenture also provide chatbot advisory and implementation services.

Key Platform Selection Criteria

Here are some key things to evaluate when choosing a conversational AI provider:

Capabilities

  • Natural language understanding – how accurately can it parse varied customer questions?
  • Contextual conversations – does it maintain context over multiple responses?
  • Built-in connectors – are key data sources pre-integrated?
  • Analytics – does it provide insights into conversation performance?

Flexibility

  • Customization – can you tailor conversations without coding?
  • Platform support – are key channels like web, mobile, messaging supported?
  • Integration – how easily can you embed bot with other apps?

Experience

  • Prebuilt content – does it offer industry or role-specific conversation templates?
  • Use cases – does the vendor have proven success cases relevant to you?
  • Customer support – are technical expertise and best practices available?

Scalability

  • Enterprise readiness – can platform handle high volumes and security needs?
  • Geographic reach – does it support your multinational requirements?
  • Roadmap – does vendor invest in continuous enhancement?

Pricing

  • Predictable pricing – are costs transparent without hidden fees?
  • Flexible plans – can you align payment model to your needs?
  • Value pricing – does perceived value outweigh pricing considerations?

Taking the time to thoroughly evaluate your options against these criteria will help ensure you choose the right chatbot platform fit for your specific needs.

Real-World Chatbot Use Cases

Here are just a few examples of chatbots delivering value across industries:

  • Sephora‘s chatbot provides a personalized skincare routine after asking just a few questions about skin type and goals.
  • 1-800-Flowers‘ chatbot Connie handles 75% of customer conversations, freeing agents for complex issues.
  • HSBC‘s chatbot addresses 200+ banking transaction questions with 85% accuracy.
  • Pizza Hut saw a 70% increase in weekly online orders after launching its Facebook Messenger bot.
  • Hyatt Hotels‘ chatbot Bookbot suggests personalized experiences and enables voice reservations.
  • Cisco‘s AI assistant Eva handles 40,000+ technical support cases per month.

These real-world examples showcase the tangible benefits – improved CX, higher sales, lower costs – that conversational AI can deliver for enterprises.

Key Takeaways

Here are the key things to remember when selecting a chatbot platform:

  • Clearly identify your use cases, goals and requirements upfront.
  • Weigh the pros and cons of self-service developer platforms vs end-to-end managed solutions.
  • Thoroughly evaluate vendor options against must-have capabilities, experience and scalability criteria.
  • Validate conversational AI value through demos and customer reference checks.
  • Start small, measure results, and expand to more use cases.
  • Partner with providers invested in continuous platform innovation.

Deploying chatbots powered by leading-edge conversational AI is a proven way to drive better customer engagement, improve efficiencies and accelerate growth. I hope this guide provides a helpful starting point for your chatbot platform selection journey!

I am Paul Christiano, a fervent explorer at the intersection of artificial intelligence, machine learning, and their broader implications for society. Renowned as a leading figure in AI safety research, my passion lies in ensuring that the exponential powers of AI are harnessed for the greater good. Throughout my career, I've grappled with the challenges of aligning machine learning systems with human ethics and values. My work is driven by a belief that as AI becomes an even more integral part of our world, it's imperative to build systems that are transparent, trustworthy, and beneficial. I'm honored to be a part of the global effort to guide AI towards a future that prioritizes safety and the betterment of humanity.

Similar Posts