Voice Bot Platforms
Voice bot platforms enable businesses to build AI-powered conversational bots. +Show More
| Products | Position | Customer satisfaction | |||
|---|---|---|---|---|---|
Qualified |
Leader
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Satisfactory
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Meet Instantly with Qualified Prospects the Moment They Land on Your Website. Real-Time Website Analytics for Sales.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
10-20 case studies
Company's number of employees
200-300 employees
Company's social media followers
10k-20k followers
Total funding
$100-250m
# of funding rounds
4
Latest funding date
April 26, 2022
Last funding amount
$50-100m
Company
Type of company
private
Founding year
2018
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IBM watsonx Assistant |
Leader
|
Satisfactory
|
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Watson Assistant is an AI assistant for businesses
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
100k-1m employees
Company's social media followers
10m-20m followers
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Haptik |
Leader
|
Satisfactory
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Haptik builds Conversational AI solutions for you to help customers find the right information at the right time through their preferred channel.
Haptik’s proprietary NLU enables most human-like conversational experience for your customers in 100+ languages, while unifying the systems and channels that you already use with its powerful integration ecosystem.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
30-40 case studies
Company's number of employees
300-400 employees
Company's social media followers
40k-50k followers
Total funding
$10-50m
# of funding rounds
2
Latest funding date
April 5, 2016
Last funding amount
$10-50m
Company
Type of company
private
Founding year
2013
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TARS |
Leader
|
Satisfactory
|
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Use Tars to make a Conversational workflow to talk to your Ad-Click Prospects.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
10-20 case studies
Company's number of employees
30-40 employees
Company's social media followers
10k-20k followers
Company
Type of company
private
Founding year
2015
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Dialogflow |
Leader
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Satisfactory
|
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Dialogflow incorporates Google's machine learning expertise and products
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
1-5 case studies
Company's number of employees
10-20 employees
Company's social media followers
4k-5k followers
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Aisera |
Challenger
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Satisfactory
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Aisera is the leading provider of AI Copilot solutions, utilizing AiseraGPT and Generative AI. Aisera's mission is to help enterprises transform their business operating model with self-service engagement by significantly reducing operational expenses, boosting revenue growth, and enabling human-like experiences. With Aisera, enterprises have the option to buy turn-key Conversational AI solutions or to accelerate the build of their own LLMs with a built-in execution engine applied to their unique customer data as part of their in-house LLM development. With 500+ integrations and 3000+ prebuilt workflows, customers achieve 75%+ automation and 90% cost reduction. Aisera has developed enterprise-wide integrations and workflows with partners that include ServiceNow, Salesforce, Zendesk, Atlassian, Workday, Microsoft, AWS, Google, Adobe, Oracle, SAP, Okta, VMware, Epic, Datadog, Splunk, Cisco, and Zoom. Some of Aisera’s enterprise customers include Zoom, Gap, Workday, Amgen, McAfee, Living Spaces, Chegg, Dave.com, Lifescan, and more. Aisera is the only Generative AI leader that has been recognized in multiple categories of the Forrester Wave™ (Chatbot for IT and Process-Centric AI for IT Operations (AIOps)) and was also awarded the Microsoft Partner of the Year award in Business Transformation. To learn more, visit www.aisera.com.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
200-300 employees
Company's social media followers
30k-40k followers
Total funding
$100-250m
# of funding rounds
4
Latest funding date
August 3, 2022
Last funding amount
$50-100m
Company
Type of company
private
Founding year
2017
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Ideta |
Challenger
|
Satisfactory
|
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
10-20 employees
Company's social media followers
2k-3k followers
Total funding
$1-5m
# of funding rounds
1
Latest funding date
July 21, 2021
Last funding amount
$1-5m
Company
Type of company
private
Founding year
2017
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Yellow.ai |
Challenger
|
Satisfactory
|
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Powers customer service operations across voice, chat and email channels with its LLM capabilities.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
400-1k employees
Company's social media followers
100k-1m followers
Total funding
$100-250m
# of funding rounds
4
Latest funding date
August 4, 2021
Last funding amount
$50-100m
Company
Type of company
private
Founding year
2016
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LivePerson Conversational Cloud |
Challenger
|
Low
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LivePerson delivers AI-powered B2C, B2B, HR, and ITSM engagement solutions that enable your brand to have conversations with millions of people as personally as you would with a single one.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
1k-2k employees
Company's social media followers
100k-1m followers
Total funding
$100-250m
# of funding rounds
6
Latest funding date
May 13, 2024
Last funding amount
$100-250m
Company
Type of company
public
Founding year
1995
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Replicant Voice |
Challenger
|
Satisfactory
|
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
1-5 case studies
Company's number of employees
200-300 employees
Company's social media followers
10k-20k followers
Total funding
$100-250m
# of funding rounds
4
Latest funding date
April 26, 2022
Last funding amount
$50-100m
Company
Type of company
private
Founding year
2017
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“-”: AIMultiple team has not yet verified that vendor provides the specified feature. AIMultiple team focuses on feature verification for top 10 vendors.
Sources
AIMultiple uses these data sources for ranking solutions and awarding badges in voice bot platforms:
Voice bots Leaders
According to the weighted combination of 4 metrics
What are voice bots
customer satisfaction leaders?
Taking into account the latest metrics outlined below, these are the current voice bots customer satisfaction leaders:
Which voice bots solution provides the most customer satisfaction?
AIMultiple uses product and service reviews from multiple review platforms in determining customer satisfaction.
While deciding a product's level of customer satisfaction, AIMultiple takes into account its number of reviews, how reviewers rate it and the recency of reviews.
- Number of reviews is important because it is easier to get a small number of high ratings than a high number of them.
- Recency is important as products are always evolving.
- Reviews older than 5 years are not taken into consideration
- older than 12 months have reduced impact in average ratings in line with their date of publishing.
What are voice bots
market leaders?
Taking into account the latest metrics outlined below, these are the current voice bots market leaders:
Which one has collected the most reviews?
AIMultiple uses multiple datapoints in identifying market leaders:
- Product line revenue (when available)
- Number of reviews
- Number of case studies
- Number and experience of employees
- Social media presence and engagement
What are the most mature voice bot platforms?
Which one has the most employees?
Which voice bots companies have the most employees?
193 employees work for a typical company in this solution category which is 170 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 21 companies with >10 employees are offering voice bot platforms. Top 3 products are developed by companies with a total of 600k employees. The largest company in this domain is IBM with more than 300,000 employees. IBM provides the voice bots solution: IBM watsonx Assistant
Insights
What are the most common words describing voice bot platforms?
This data is collected from customer reviews for all voice bots companies. The most positive word describing voice bot platforms is “Easy to use” that is used in 9% of the reviews. The most negative one is “Difficult” with which is used in 2% of all the voice bots reviews.
What is the average customer size?
According to customer reviews, most common company size for voice bots customers is 51-1,000 employees. Customers with 51-1,000 employees make up 40% of voice bots customers. For an average Conversational AI solution, customers with 51-1,000 employees make up 35% of total customers.
Customer Evaluation
These scores are the average scores collected from customer reviews for all voice bot platforms. Voice Bot Platforms are most positively evaluated in terms of "Customer Service" but falls behind in "Likelihood to Recommend".
Where are voice bots vendors' HQs located?
Trends
What is the level of interest in voice bot platforms?
This category was searched on average for 4.4k times per month on search engines in 2024. This number has decreased to 0 in 2025. If we compare with other conversational ai solutions, a typical solution was searched 612 times in 2024 and this decreased to 0 in 2025.
Learn more about Voice Bot Platforms
Voice bots, also called voice-enabled chatbots, are AI-based software that take voice commands and reply by voice. They enable users to communicate faster compared to text based bots. Popular examples of voice bots Apple’s Siri, Amazon Alexa and Google Assistant. There are two types of voice bots:
- Hybrid model: Voice and text controlled bots.
- Voice-only bots: Only Voice-controlled bots.
Like chatbots, voice bots are able to not just recognize what the user says but to understand the customer’s intent and have two-way communication to solve the users’ problems. In addition to the technologies used in text based bots, voice bots also rely on transcription to first get user's commands in text form. They also rely on text-to-speech conversion to talk to users.
Voice bots work like text chatbots. For more information about chatbots you can visit our research on chatbots. An additional voice recognition step is required in voice bots compared to chatbots.
The steps can be summarized roughly:
1-Voice input is taken from the user with a device like a mobile phone or computer with a microphone.
2-This input is sent to the cloud in order to decode the message and understand the user intent.
3-The audio message is converted to text and the natural language processing models analyze the users’ requests.
4- The AI-based engines search for the most suitable answers or actions and create a response.
5-The answer is converted audio and shared with the user.
Using voice bots provide a better, more natural user interface. Companies can use voice bots to reduce call center costs and create more user friendly products.
The increase in mobile users results in an increase in the voice bot demand: Mobile devices provide ease of use in terms of voice applications. It is faster to describe any problem by talking than typing. The progression of speech and voice recognition technologies are supported by tech giants including Google, Apple, Microsoft and Amazon, as well as Baidu, Xiaomi and Alibaba.
Voice-bot adds value to contact centers by reducing queue time and therefore improving customer satisfaction. The problem-solving process of users with call center takes less time than the waiting period. By working 24/7 and with the ability to scale up according to demand, voice-bots eliminate wait times.
The market size is increasing as the demand for chatbots and voice bots: IBM points out that businesses spend $1.3 trillion on 265 billion customer service calls each year. The process can be automated partially by using voice bots.
There are two main reasons why voice bots are preferred to chatbots.
Speaking is a faster way to explain a problem than typing: Especially for older people, typing is slower than talking in describing a problem. On the other hand, according to PWC research, younger people tend to use voice assistants. It shows that voice bots are more useful for both younger and older people in terms of ease of use and faster communication.
People tend to prefer a human-like interaction to tell their problems: Voice bots provide smoother, more human-like interactions
Many tech giants invested in voice technologies in recent years. A disadvantage of voice bot over textual chatbots is the speech recognition time. With the advances in both natural language understanding and speech recognition technologies, launching a voice bot is not significantly more challenging than launching a text based chatbot.
There are four different points to consider while choosing a voice bot provider.
- NLU capabilities: The NLU infrastructure sets the boundaries of what a voice bot can do. At this point, there may be a tradeoff between price and NLU capabilities. The optimal NLU skills should be chosen by considering the requirements of the use case.
- Deployment: The training process of AI used by the voice bot must be completed in order to minimize the time required for full integration. Installation of the voice bot into system and without being fully trained can cause problems such as user satisfaction and security. A trained AI can reduce time of deployment.
- Use cases: It is necessary to determine exactly what purpose voice bot to use. It is necessary to determine exactly what purpose voice bot to use. For example, an IVR bot should not have to have complex NLU. Taking different types of work over the same voice-bot increases the likelihood of errors. Therefore, it may be more suitable to choose an application-specific bot.
- Pricing: Voice bots have different payment models, just like chatbots. Options such as monthly plan, pay per use, pay per performance may be available. At this point, a payment plan should be selected considering how much the boat will be used. However, in most cases performance-oriented payment plans may be a viable option.