Sold by: NLX
Deployed on AWS
Vendor Insights
Build, manage, and analyze all your conversational AI applications in one place.
4.2
Overview
NLX offers the most comprehensive, end-to-end conversational AI platform for everyone - from individual builders to large enterprise brands. Our platform empowers you to build not only powerful but beautiful world-class multimodal (chat, voice, and Voice+™) experiences. Sitting at the intersection of conversational and generative AI, our no-code platform makes it easy for all users, regardless of technical expertise, to build, manage, and analyze automated conversations across any combination of channels.
The NLX platform is incredibly flexible, designed to handle even the most unique challenges with out-of-the-box or custom solutions. It seamlessly integrates with all your existing channels, systems, and unique business processes. We also provide customizable analytics and alerting capabilities to eliminate guesswork, giving you peace of mind that your customers are always getting the best possible automated experience.
Key features include:
- Integrations with Amazon Bedrock, Anthropic, and other Enterprise LLMs
- Access to Voice+, our patented multimodal voice technology
- Improved intent detection accuracy of standard NLPs
- Generative responses from knowledge sources that you trust
- Channel grouping for single-flow multichannel deployment
- Customizable multimodal (chat, voice, and Voice+) self-service experiences
- Seamless personalization for more satisfying conversations with Touchpoint
- Generative-AI-powered conversation builder
Highlights
- Design all conversations visually in a simple, no-code canvas
- Build faster with thoughtful generative AI-powered features
- Deploy one-step integrations with Amazon Connect, Amazon Bedrock, Amazon Chime SDK, and Amazon Lex
Details
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Buyer guide
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Financing for AWS Marketplace purchases
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/unit |
|---|---|---|
Chat conversation | Chat conversation | $0.20 |
Voice conversation | Voice conversation | $0.20 |
Multimodal conversation | Multimodal conversation | $0.20 |
Monthly subscription | Monthly subscription fee for access to the platform | $0.00 |
Conversation | Chat, voice, and multimodal AI conversations | $0.20 |
Conversation (Overage) | Overage fee for chat, voice, and multimodal AI conversations | $0.00 |
Agentic Execution | Agentic execution | $0.10 |
Vendor refund policy
Since we charge on a Pay-As-You-Go manner, we do not typically offer refunds. We do recognize that special circumstances can occur and we are happy to assist you. Should you feel that you were wrongfully charged, please reach out to support@nlx.ai and we'd be happy to assist you.
Custom pricing options
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Delivery details
Software as a Service (SaaS)
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Resources
Vendor resources
Support
Vendor support
You can reach us through the Support page in the NLX platform. support@nlx.ai
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
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Positive reviews
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Negative reviews
AI generated from product descriptions
Large Language Model Integration
Integrations with Amazon Bedrock, Anthropic, and other Enterprise LLMs for powering conversational responses
Multimodal Communication Channels
Support for chat, voice, and Voice+ (patented multimodal voice technology) across multiple channels with single-flow deployment
No-Code Conversation Design
Visual conversation builder with no-code canvas for designing and managing conversational flows without requiring technical expertise
Intent Detection and Natural Language Processing
Improved intent detection accuracy compared to standard NLP systems for better understanding of user inputs
Customizable Analytics and Alerting
Customizable analytics and alerting capabilities for monitoring and analyzing conversational AI application performance
Omnichannel Engagement Platform
Native omnichannel engagement applications including voice engagement, studio and routing capabilities for customer interactions across multiple channels
AI-Powered Automation
AI-powered virtual agents, agent assist, AI trainer, and generative AI solutions for automating customer service processes and enhancing agent capabilities
Unified Analytics and Reporting
Integrated customer experience analytics with live and explore standard reporting, dashboards, and workflows accessible through a single pane of glass interface
Workforce and Knowledge Management
Workforce engagement management, employee collaboration tools, and knowledge management capabilities with over 70 out-of-the-box integrations
API Access and Extensibility
API access and open platform architecture with a common data model enabling custom integrations and extensions
Natural Language Understanding
Proprietary Large Language Model (ConveRT) pre-trained specifically for customer service applications enabling accurate understanding of customer inquiries
Spoken Language Recognition
Advanced speech recognition technology designed to understand callers regardless of accents, dialects, background noise, and variations in speech patterns
Conversational Interaction Model
Customer-led dialogue system allowing callers to speak naturally, interrupt, ask questions, and navigate between different topics without keyword guessing
Multi-language Support
Support for multiple languages and linguistic variations enabling deployment across diverse customer bases
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
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Customer reviews
Nasr Ullah
Omnichannel virtual assistance has improved support efficiency but still needs better context handling
Reviewed on Aug 02, 2026
Review from a verified AWS customer
What is our primary use case?
I have been exploring Conversations by NLX in a couple of my projects around three to four months back. My exploration was conversational and analytical to improve our customer's projects. Basically, I use Conversations by NLX for omnichannel support and integration with our team's systems.
What is most valuable?
Conversations by NLX offers a visual conversation builder that is intuitive and allows both technical and non-technical users to collaborate with end-to-end recognition and conversation flow management of design, making customer interactions feel more natural.
Conversations by NLX is easy to integrate with back-end services, APIs, and authentication, so integration flexibility stands out to me.
The architectures of Conversations by NLX appear suitable for organizations handling high interaction volumes.
I see that Conversations by NLX provides analytics and continuous improvements, which are valuable.
Conversations by NLX functions as a virtual assistant across customer support channels. Customers come through different inquiries and integrate with diagnostic data at runtime, which helps address their needs.
Conversations by NLX is replacing our chatbot and agents that we were using with in-person customer representatives.
What needs improvement?
I think context-wise, if Conversations by NLX could improve to maintain consistent context, that would be beneficial.
If someone is in a conversation and things are added when it came to the customer support journey, the discussions can become lengthy, and it loses the context of understanding, maybe asking for repetition of things. This is one concern with Conversations by NLX.
Another concern is the volume of data. In customer support when dealing with enterprise customers, for example, if an organization has 50,000 employees requiring support for their hardware from different vendors, there is massive data coming in. The response time in terms of calculating and querying could be improved. If the efficiency can increase, that would be helpful.
Because Conversations by NLX is mostly covering standard cases and some edge cases, there are many competitors in the market available now. I would check the quality of the response, the response time in terms of scalability, and different contexts. These are areas where improvement would be beneficial.
For how long have I used the solution?
I have been working in my current field for the past 20 years.
What do I think about the stability of the solution?
Conversations by NLX is stable in my experience, though there is sometimes downtime or issues.
What do I think about the scalability of the solution?
Conversations by NLX sometimes faces difficulties regarding scalability, though sometimes it performs fine.
How are customer service and support?
I am satisfied with the customer support for Conversations by NLX. I would rate the customer support for Conversations by NLX an eight on a scale of one to ten.
Which solution did I use previously and why did I switch?
I explored many systems before Conversations by NLX, including Sierra, Zoom, and others in the marketplace. It was an exploration journey where I checked which system is the best.
Before choosing Conversations by NLX, I worked with Sierra, Zoom, and OpenAI.
How was the initial setup?
My experience with pricing, setup cost, and licensing for Conversations by NLX seems fine.
What was our ROI?
Conversations by NLX is worthwhile. It is money-saving and time-saving as well.
Which other solutions did I evaluate?
I am not interested in being a reference for this vendor.
There is a market that is diverging, and every day new things are coming. OpenAI is on its way, and there are many big players in the market right now. The efficiency, accuracy, and response time all matter for Conversations by NLX. The things which I mentioned are relevant as per the latest trends and new market competitors coming, and it would be appreciated if Conversations by NLX could follow or exceed the trending values and metrics.
What other advice do I have?
Regarding Conversations by NLX's governance and security, I have implemented a security perspective to secure our own data.
Accuracy-wise with Conversations by NLX, it is around 88% to 92%. I cannot give a fixed number, but it varies. Sometimes it is correct, and sometimes it is not exact to what I am looking for, but overall it is fine.
They mentioned that there is some incentive regarding Conversations by NLX, but I do not know what I will get or not.
I would appreciate more information on rollback management or rollback handling and which particular LLMs are supported for that feature.
My overall review rating for Conversations by NLX is seven.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Garimakaushik Kaushik
Multimodal AI has streamlined multilingual red teaming and has improved guided voice journeys
Reviewed on Jul 28, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Conversations by NLX is for multimodality experiences such as chat, voice, and text, as well as enterprise use cases with low code or some integrations, with different multilingual support. My role has a lot to do with testing different languages, so multilingual support is something I'm looking for.
I can give a specific example of how I used Conversations by NLX in one of my projects, where I'm particularly looking for differences between sarcasm, humor, and satire, and how it would respond to different things in different languages, as well as in different categories such as violent crimes and non-violent crimes. When we're doing adversarial or safety testing to check how strong the AI is, that's part of the red teaming effort that we are doing. We try different techniques, including different prompts which could trick the AI. The multilingual analysis of the prompt outputs in various categories is a critical aspect.
What is most valuable?
The best features that Conversations by NLX offers are voice and the multimodality experiences, especially for guided customer journeys across voice and digital channels.
Guided customer journeys across voice and digital channels are valuable for my team because we are a team of red teamers who do adversarial testing, and it really matters how it gives its output across different cultures, different languages, and different countries. It really has to stand out how the tools handle one channel well or if they're doing a great job connecting the experiences across different channels in one flow. Conversations by NLX positions voice to reduce friction and make the interaction feel much more seamless, especially for customers who really need step-by-step help.
Conversations by NLX has impacted my organization positively as a real differentiator for us because we do side-by-side testing for many AI models, and the multimodality experience in Conversations by NLX allows the customer to interact in more than one way during the same task, such as speaking while also seeing the prompts, choices, and confirmations. That has made a huge impact.
What needs improvement?
Conversations by NLX could improve on some advanced use cases, as they might need help with the technical setup and integration. That could be one downside, and sometimes it feels more enterprise-focused than a very beginner-friendly or lightweight tool. Some work in that area could be beneficial.
The pricing and implementation details of Conversations by NLX are not fully transparent upfront, so evaluation may require a sales conversation.
For how long have I used the solution?
I have been using Conversations by NLX for almost a year.
What do I think about the stability of the solution?
Conversations by NLX is stable.
What do I think about the scalability of the solution?
Conversations by NLX's scalability is pretty good, and they are very scalable.
How are customer service and support?
Customer support for Conversations by NLX is good. Scalability is one of the main strengths, and if I've ever needed customer support, I've had a lot of support with customer interactions. I would rate the customer support for Conversations by NLX on a scale of one to ten as a ten.
Which solution did I use previously and why did I switch?
I did previously use a different solution; however, this information is discreet, and I cannot share that. We did use a different solution at Google.
How was the initial setup?
My experience with Conversations by NLX regarding pricing, setup cost, and licensing is that I'm not the one who is mainly in charge, but the pricing and implementation details were not very fully transparent upfront.
What about the implementation team?
My company does not have a business relationship with Conversations by NLX other than being a customer; there is no relationship.
What was our ROI?
I have seen a return on investment with Conversations by NLX. We definitely saved money and time, but there were no staff that had to be let go because of Conversations by NLX. However, we could handle more projects because of it, so efficiency and time definitely improved.
What's my experience with pricing, setup cost, and licensing?
The pricing and implementation details of Conversations by NLX are not fully transparent upfront, so evaluation may require a sales conversation.
Which other solutions did I evaluate?
Before choosing Conversations by NLX, I evaluated other options, and we evaluated many different options, even including Perplexity and Copilot.
What other advice do I have?
The advice I would give to others looking into using Conversations by NLX is that they are pretty scalable, stable, accurate, relevant, and safe. I think everybody should use it.
If anybody needs a scalable, enterprise-grade conversational AI, they should go for Conversations by NLX. It looks pretty solid.
Conversations by NLX's governance and security look pretty secure, though I've never thought deeply about this parameter. It looks pretty solid on paper. They do call out the access control, the sensitive data handling, integrations, and runtime protections. For governance, I feel it's reasonably mature in the sense that the platform supports reviewability and operational oversight, but I would still want to verify practical details in the real deployment.
Regarding Conversations by NLX's AI capabilities, I feel they are accurate and reliable; almost nine out of ten times, it's accurate and pretty reliable, and the output is relevant, very consistent, and complete. I would rate this review overall as an eight out of ten.
Sankalp Verma
Automating customer banking requests has improved support while AI security still needs deeper review
Reviewed on Jul 23, 2026
Review provided by PeerSpot
What is our primary use case?
Conversations by NLX is used for customers to get account details, card details, to block a card, or for loans, to get loan details, and to get a checkbook request or locate a bank branch.
We create a flow to do the task with Conversations by NLX by dragging and dropping and making a flow to accomplish this, and integrating APIs and REST APIs from the backend core banking APIs to authenticate the user or the customer. We can then proceed with the main task. For example, if a customer wants to block a debit card or wants any details, we can create a flow by creating the intents and entities. This defines what the user wants and what we are looking for. We can ask the required questions and create entities such as customer ID or registered mobile number as per the project requirements and specifics.
What is most valuable?
Conversations by NLX is user-friendly, easy to use, and environment-friendly, making it a good platform.
The drag-and-drop functionality of Conversations by NLX is easy to use. The environment is user-friendly, and we don't have to do much coding.
Conversations by NLX has helped us to assist our users and customers and develop our product for the contact center platforms.
What needs improvement?
I haven't used Conversations by NLX much, so I don't think there's an improvement needed.
Regarding Conversations by NLX's AI capabilities, the security is solid. I haven't done a deep dive into security for specific purposes, but it's secure and the authentication aspects were great.
For how long have I used the solution?
I have been working with this solution for the past four years.
How are customer service and support?
I am quite satisfied with the product we developed on Conversations by NLX.
Which other solutions did I evaluate?
We haven't had a partnership with another company. We are using a paid version.
What other advice do I have?
Conversations by NLX is quite a good platform, and that's the main reason I have chosen it. It's easy to use, user-friendly, and you don't have to struggle to work on it. My overall rating for Conversations by NLX is seven to eight out of ten.
AbdulWaheed
Dynamic conversations have improved self-service options and provide human-native voice choices
Reviewed on Jul 22, 2026
Review from a verified AWS customer
What is our primary use case?
One of the reasons I explored Conversations by NLX was to investigate the platform's capabilities, as I was in a role to evaluate different platforms that provide conversational AI solutions. Conversations by NLX came into that search, and I have thoroughly explored this platform.
We were looking for a platform where we have the flexibility to choose between different models. We have different subscriptions at the company level, and we wanted to see which one would work better for us. Additionally, the flexibility to choose between different voices was important to us. We have our custom voices and corporate voices as well. These were the main things I was exploring in the first phase.
I have recently learned that Conversations by NLX is part of Amazon Connect. This was one of the reasons we considered it, because at Deutsche Telekom we were also exploring the migration from Cisco to Amazon Connect. That's the reason we got Conversations by NLX into our consideration.
We currently have a hybrid cloud setup and we have a requirement for private cloud as well, but we would like to see how Conversations by NLX could be integrated there.
What is most valuable?
Conversations by NLX offers human-native voices, a variety of models, flexibility to build, test, and deploy applications, and ease of use on the platform.
With conversational AI, we have the flexibility that we do not have to draw the IVR applications in a static way. Everything is dynamic and according to what the customer wants and asks. They can ask anything, any flow, anytime while being on the conversation.
With a Conversations by NLX solution, we can achieve more automation of different use cases. We have self-service applications which were previously limited, and now we have increased these significantly because our customers are asking for a lot more self-service features.
What needs improvement?
The possibility to have Conversations by NLX on-premises would be beneficial because I have not seen that Conversations by NLX is providing an on-premises solution. In our cases, we have some sensitive helplines where we do not want to put the data on the internet and we prefer to have everything within our network.
I think the compliance for Conversations by NLX could be checked a little more thoroughly, and the data privacy should be stronger because the European laws are much more focused towards data privacy and data residency.
For how long have I used the solution?
I have not used Conversations by NLX extensively, but I have reviewed the introductory materials. I am not an expert on Conversations by NLX, but I have gone through a couple of the documentation resources.
What do I think about the stability of the solution?
Conversations by NLX is stable from what I have seen and tested. The stability has been satisfactory, and we were able to quickly test things and evaluate Conversations by NLX platform.
What do I think about the scalability of the solution?
The scalability of Conversations by NLX is also fine. As I mentioned, we have not tested it in production, but we have evaluated it from an evaluation perspective and we were satisfied with the scalability as well.
How are customer service and support?
The customer support from Conversations by NLX was great. We had a couple of questions while setting up the environment and during onboarding. The team was very quick, and we were able to get responses within a couple of hours.
How was the initial setup?
We have not used Conversations by NLX in production. We were using it only for the test environment where we sent a couple of requests on the platform and tried to see how human-native the responses are. We were satisfied with the response, but we have not put this in production.
Which other solutions did I evaluate?
We evaluated a couple of different solutions. During the evaluations, we went through Vapi and Parloa, which is a Berlin-based company. We were also exploring different open-source solutions as well.
What other advice do I have?
Amazon Connect lives in a very big ecosystem from AWS. What they were lacking was the capability of human-native voices. I think Conversations by NLX would work for that with this partnership.
I would rate the customer support of Conversations by NLX as an eight on a scale of one to ten.
I would rate Conversations by NLX eight out of ten because of the platform flexibility, the documentation and help we receive, and the feature set.
We used to have a lot of concerns about Conversations by NLX's AI capabilities, governance, and security because we are basically European telecom providers, and we prefer to have everything GDPR compliant and are really concerned about data privacy. We reviewed the things provided by Conversations by NLX, and we were quite satisfied with that. My overall review rating for Conversations by NLX is eight out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
SumitSingh3
Chatbots have improved ticket and flight support while channel coverage still needs to grow
Reviewed on Jul 22, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for Conversations by NLX is that we are working in the aviation domain, developing a customer-related chatbot product for our employer and for our internal employees to provide information related to canceling tickets, booking tickets, or receiving notifications related to them.
A specific example of how I am using Conversations by NLX is that we developed one chatbot where employees are engaged. We use the chatbot to provide information related to booking, flight takeoff, or landing information, and employees can update their own seats. These are the types of information we have provided using this project, and these are the problem statements we are including in Conversations by NLX, with multiple business logics and logical problem-solving that we have used to solve these problems.
What is most valuable?
The best features Conversations by NLX offers include logical thinking; if you implement your business problem, you can easily use the drag and drop feature to implement the conversation, and these are the basic things I have mostly used.
I have used features including customer information-related analytics. We have provided data based on that, and we have analyzed customer CSAT and customer satisfaction requirements. Regarding the integration, we have implemented on multiple platforms, such as web and mobile bases including iOS and Android.
Conversations by NLX has positively impacted my organization because before using it, we used other customized platforms to build our chatbots. We developed more than fifty chatbots using Conversations by NLX, which provides mostly friendly and very easy to implement functionality. You can easily integrate it with multiple environments and systems, analyze customer data, and receive notifications from the customer end very easily.
What needs improvement?
From my perspective, it would be helpful if you could integrate Conversations by NLX with multiple channels to create a more friendly and reachable product. If you implement any bot or system and reach multiple persons, your product can already reach many customers as well as employees. Therefore, if multiple channels can be added, it would be very helpful.
For how long have I used the solution?
I have mostly worked in my current field for more than ten years.
What do I think about the stability of the solution?
Conversations by NLX is a stable platform, and I can confidently say that.
What do I think about the scalability of the solution?
Regarding Conversations by NLX's scalability, I find that if you are implementing any application or bot, it can scale your application related to performance and influence, depending on the questions asked. From my perspective, it is good with a good experience.
How are customer service and support?
Customer support from Conversations by NLX is good from my end.
Which solution did I use previously and why did I switch?
We previously used multiple solutions including Salesforce Einstein Bot, Kore.ai, and Yellow.ai. These were almost good, but there are some new things in Conversations by NLX. It is easy to implement, easy to integrate, and easy to analyze, leading to a higher satisfaction rate from the customer side; these are the good things we get from Conversations by NLX.
What was our ROI?
I have seen a return on investment as it saves more time; related to money, I have also saved costs associated with employees' time. As the one who implements it, I can say it saves more time, and I have experience with that.
What's my experience with pricing, setup cost, and licensing?
Regarding my experience with pricing, setup costs, and licensing, I am the one implementing it, so I do not have much knowledge about the setup cost, licensing, and pricing related to it.
What other advice do I have?
I have not mostly found things lacking in Conversations by NLX because based on our needs, it provides what we require. Therefore, based on that and our business logic, we can implement the code everywhere. I do not think any integration, customer satisfaction, or analysis is required as we currently get all that we need.
Conversations by NLX is good and does not need any improvements that I have not mentioned yet.
I have already provided advice to multiple persons that using Conversations by NLX saves your time and money as well. I would rate this review a 7.5 overall.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)