The Forrester Wave™: Conversational AI For Customer Service, Q2 2024

Conversational AI For Customer Service Vendor Product Comparisons 2024

Key features and pros and cons of top Conversational AI For Customer Service products:

Amelia - Leaders

Pros:

Deep conversational AI history with over 25 years in the market and consistent mastery of new technology
Aggressive adoption of new AI technologies using LLMs and genAI to improve customer self-service
Pricing charges per successful interaction with specific measures of success, aligning with customers
Integrated LLM and genAI for knowledge access and summarization with tools to identify, manage, and sync source documents
Development environment helps define digital UI components and efficiently leverages different channel capabilities
Strong partner network through partnerships with core contact center providers like NICE

Cons:

Reference customers reported that application development on the system can be complex, potentially requiring external professional services
References reported the product can be expensive to own
High-touch approach may be more suitable for large brands rather than small to midsize organizations

Cognigy - Leaders

Pros:

Flexible, scalable microservices and Kubernetes-based architecture deployable on-premises, private cloud, or SaaS on any hyperscaler
Uses session information, user input, and context to drive how LLMs and genAI are employed beyond just calling them
LLMs used as genAI guardrails, running checks to ensure appropriate answers
Strong partner support resources with robust partner marketplace enabling significant partner sales
Reference customers complimented development environment for usefulness to both programmers and nonprogrammers
Roadmap includes advanced genAI orchestration and more powerful personalized knowledge management capabilities

Cons:

Reporting systems do not allow for inclusion of external data, limiting business insights the product can provide
Punches above its weight through partners but may have less direct market presence than some competitors

Kore.ai - Leaders

Pros:

Early and intelligent incorporation of genAI into solutions with strong XO platform framework
GALE AI application framework enhances integration of modern AI functionality
Global partner ecosystem with self-paced academy for training and certification
Leading omnichannel features, modern security and trust capabilities, and excellent digital user experience
Reference customers praised development tools and prebuilt applications
Significant investments in roadmap including better LLM orchestration and autonomous agents
Serves brands across healthcare, financial services, retail, and more

Cons:

Uptime numbers are only in the middle of the pack among vendors in this evaluation

OneReach.ai - Leaders

Pros:

Intelligent Digital Workers (IDWs) use LLMs and genAI to do real work for customers
Customers praised support and deployment teams as mentors who help master new AI technologies
Strong commitment to design that helps deliver standout self-service applications
Development environment is truly no-code with 80% of developers having no coding experience
Can define complex tasks like array management without needing to code
Deploys only in private SaaS model with microservices and Kubernetes approach delivering strong data protection and leading uptime
Reference customers praised ease of use of development tools

Cons:

Struggles to find the right mix of partner support to expand market reach
While it has had occasional successes with key partners, partner ecosystem is less robust than some competitors
Some reference customers experienced limitations due to their own internal issues rather than OneReach.ai problems

Aisera - Strong Performers

Pros:

Fast-growing company that nearly doubled customer base in 2023
Step-by-step deployment approach identifying specific ROI goals and meeting quarterly with customers
TRAPS framework protects data confidentiality and user privacy while reducing hallucinations and removing bias
AiseraGPT delivers stellar uptime numbers reflecting quality system architecture
Provides own SIP gateway for better integration into customers' telephony environments
Roadmap includes extending LLM utilization, AI-driven search additions, and building new foundation model

Cons:

Tools for enabling system administrators to generate alerts fall short
Pricing approach is broad and defined on a customer-by-customer basis, which may lack transparency

Amelia - Leaders

Pros:

Deep conversational AI history with over 25 years in the market and consistent mastery of new technology
Aggressive adoption of new AI technologies using LLMs and genAI to improve customer self-service
Pricing charges per successful interaction with specific measures of success, aligning with customers
Integrated LLM and genAI for knowledge access and summarization with tools to identify, manage, and sync source documents
Development environment helps define digital UI components and efficiently leverages different channel capabilities
Strong partner network through partnerships with core contact center providers like NICE

Cons:

Reference customers reported that application development on the system can be complex, potentially requiring external professional services
References reported the product can be expensive to own
High-touch approach may be more suitable for large brands rather than small to midsize organizations

Avaamo - Strong Performers

Pros:

Delivers complex customer service applications to large enterprises at scale
Strong core platform available globally with full redundancy, active/active disaster recovery, and rolling updates
Integration strength helps gather data for personalized interactions
Tools enable applications to operate in both voice and digital channels
Supports multimodal applications where customers can interact on two channels simultaneously
Works selectively with specific technology and implementation partners to ensure success

Cons:

Reference customers provided feedback that reporting and administrative functions fell short of their needs
Alerting functionality is limited
Focus on high end can create product gaps that may impact smaller customers

LivePerson - Strong Performers

Pros:

Almost 30 years of experience in customer self-service market with strong name recognition
Strong partner ecosystem and unique, broad product offerings
Enables differentiated customer experience across self- and assisted service
Over 70% of customer interactions in 2023 included a chatbot
Meaningful Automated Conversation Score (MACS) helps brands manage customer experiences by grading every interaction
Strong digital capabilities for both assisted and self-service interactions

Cons:

Integration of LLMs and genAI is not as deep as other vendors in evaluation
Reference customers commented that company lags in LLM and genAI areas
Product currently requires three different development environments to build robust self-service application
Products are in transition to newer AI technologies

Netomi - Strong Performers

Pros:

Strong vision for genAI as the new customer interface
High customer retention rates with raves from references
Conversation OS platform boasts strong tools for application development and intent creation
Sanctioned AI provides guardrails ensuring accurate and appropriate answers from knowledge base
Prebuilt integrations with key back-end systems like CRMs
Platform integrates with many iPaaS providers
Reference customers hailed 'cutting-edge tech' and 'unparalleled service'
Building accelerators for genAI assistants to speed up development

Cons:

As one of the smaller vendors, R&D budget is limited which may make it hard to keep up in changing market
Uptime numbers in 2023 were below par compared to other vendors in evaluation
Integrations with LLMs and genAI lack the polish of Leaders' integrations

Omilia - Strong Performers

Pros:

Longtime player in IVR and voice self-service with natural language dialog manager from 2009 and speech-to-text platform from 2010
Omilia Cloud Platform delivers advanced speech technology and powerful telephony connectivity
Uses LLMs and genAI to expand breadth of voice self-service
Reference customers praised relationship with company calling support 'unparalleled' and 'unwavering'
Stellar customer retention rates underscore value of customer focus
Roadmap heavily focused on genAI and RAG for knowledge management

Cons:

Approach leans more heavily on automation than human element, resulting in lower vision and innovation scores
Relatively small R&D budget will make it challenging to keep pace in volatile market
Holes in support for LLMs and genAI - summarization and RAG synthesis currently only in beta
Multiple customers identified reporting as needing improvement with need for better insights and more reports on prebuilt applications

Sprinklr - Strong Performers

Pros:

Background in marketing and social media leads to innovative approaches like business value realization deployment methodology
Single microservices-based platform with no functionality added through acquisition
Conversational AI platform leverages core omnichannel capabilities for better customer experiences
Comprehensive no-code development environment
Reference customers praised support and service teams
Manages customer self-service as part of broader customer experience approach

Cons:

Partner support capabilities are relatively new and less mature than others in evaluation
Breadth of tools available can be overwhelming at times
Reference customers mentioned product is complex and takes a while to comprehend

Ada - Contenders

Pros:

Unique all-in approach using exclusively fine-tuned LLMs from Anthropic, Microsoft, and OpenAI
Bold approach helps brands quickly deliver highly functional conversational AI applications
Innovative pricing per 'automated resolution' checking CSAT and containment, using LLMs to decide success
LLMs deeply integrated into Ada platform, reporting, and development tools simplifying development and administration
Alerts system owners when automation rates are falling making metrics more valuable
Pricing approach aligns Ada with customers' needs

Cons:

Overall current offering has gaps and lacks polish of other vendors
Customer references complained about costs from heavy reliance on genAI
One reference stated 'Some simple things are too hard'
Early days for proof points on all-genAI approach

Verint - Contenders

Pros:

Mastered art of recruiting and supporting partners giving massive worldwide presence
Proven product with scalable and reliable architecture shown through positive uptime numbers
Centralized Da Vinci function for AI-powered bots enhances analytics, assists agents, and drives better service
Built infrastructure for RAG-based answer creation
Reference customers praised quality of support and service teams and overall expertise
Wide breadth of AI solutions for customer service

Cons:

Centralized Da Vinci approach hurts flexibility and slows speed of delivering conversational AI functionality
Some tools for building applications still under development
Reference customers identified challenges that come from working with large organization
Roadmap includes catch-up work around integrating genAI into conversational workflows

Yellow.ai - Contenders

Pros:

Grown quickly by selling to smaller organizations many vendors cannot serve
New YellowG platform adds genAI to microservices-based platform
Development environment provides forms to assist in building genAI prompts simplifying application development
Offers AI-driven FAQ interactions from variety of source documents and knowledge retrieval for answer management
Reference customers raved about responsiveness to needs and partner-like treatment
Cost-effective solution for target market

Cons:

Historically not focused on partner sales, currently building partner network
Aggressive vision including moving upmarket and massively expanding product breadth may lead to shallow products
Roadmap includes building CRM, full AI-powered CCaaS product, and conversation analytics which may stretch resources
Reported uptime numbers lower than most vendors in evaluation

eGain - Challengers

Pros:

Well-known player in digital customer service since 1997 with long history building conversational AI solutions
Strong partner support program and high customer retention rates
Proven, scalable, solid product in production for many years
Great tools for knowledge management and summarization of back-end content
Positive overlaps between knowledge management and conversational AI capabilities

Cons:

Company's attention shifting heavily toward knowledge management at expense of conversational AI
Roadmap shows ongoing commitment to knowledge management direction
Conversational AI offering suffers from less focused approach to development
Less attractive for brands looking for holistic conversational AI solution taking full advantage of genAI
Orchestrating LLMs and genAI systems at runtime is particularly weak

FAQs

Q: Which vendors are Leaders in 2024?

A: Amelia, Cognigy, Kore.ai, OneReach.ai

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders in the Forrester Wave for Conversational AI for Customer Service demonstrate superior current offerings and strong strategies. They excel at orchestrating AI systems, CRMs, and communications channels to get work done, provide comprehensive tools for building quality self-service applications, and deliver modern, reliable, safe, and manageable platforms. Leaders differentiate through mastering the art of orchestrating multiple AI assets to deliver smarter, more useful chatbots and intelligent virtual assistants (IVAs). They go beyond basic no-code tools to provide environments that maximize efficiency of both coders and noncoders, offer useful prebuilt modules, provide robust partner and developer ecosystems, deliver high uptime and agile scalability, and use multipronged tools and approaches to battle concerns related to genAI challenges like hallucinations, bias, and jailbreaking.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for Conversational AI For Customer Service in 2024

Conversational AI For Customer Service Vendor Product Comparisons 2024

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FAQs

Q: Which vendors are Leaders in 2024?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

Reference