Conversations by NLX Reviews

We used Conversations by NLX during one of our POC initiations to automate our tier-one customer support, handling everything from basic troubleshooting to order status inquiries. It integrated smoothly with our backend systems, so the automated flows have access to real-time data.

A great example of how Conversations by NLX automation helped our Taiwan customer support was during a major regional product promotion in Taiwan last quarter. Our local support queue usually gets completely slammed with routine inquiries about shipping timelines and promotional code glitches. Before Conversations by NLX, our small, Taipei-based team would get buried under a mountain of identical tickets. We deployed Conversations by NLX with a localized automated flow in Traditional Chinese. It handled 65% of those incoming tier-one inquiries right out of the gate, verified the customer IDs, and had the real-time tracking data from our logistics backend.

We noticed a drop in average wait times for customers, as the automated flows handle a large portion of routine questions immediately. It also relieved a lot of pressure on our support team, allowing them to dedicate more bandwidth to complex, nuanced issues. Overall, it has really helped us scale our operations efficiently.

Conversations by NLX fits seamlessly into our existing CRM. When the bot is not able to resolve an issue, it performs a warm handoff to a live agent, passing the full context of the conversation so that the customer never has to repeat themselves. Combined with their analytics dashboard, we are constantly refining our flows based on real-time data, making our workflow more effective every single day.

The ability to handle complex and multimodal conversations seamlessly is one of the key things that Conversations by NLX offers. The interaction feels natural, whether it is through voice, text, or visual elements. It has a good analytics dashboard that gives real-time insights into customer behavior and helps pinpoint exactly where people might be stuck in the flow.

The analytics dashboard of Conversations by NLX is the true daily driver. While the multimodal conversation handles what makes the magic happen for the customer, the dashboard is where we do the heavy lifting to see how well it is actually performing. It also allows us to spot trends, see exactly where users might be dropping off, and make real-time adjustments to improve the flow. This is essential for keeping our support as effective as possible.

One area for improvement in Conversations by NLX would be the initial learning curve for setting up some of the more advanced integrations with our older legacy systems. We occasionally encounter small hiccups where the bot has trouble maintaining context across a very long, multi-turn conversation. Having even more robust, out-of-the-box reporting features would also be a fantastic addition for deeper analysis.

More comprehensive documentation for Conversations by NLX with more detailed code examples and a more centralized developer hub would make the initial development and debugging process much smoother.

The main things holding Conversations by NLX back from a higher score of 9 or 10 are the hurdles we faced during the initial setup with our old legacy systems and the need for more in-depth documentation to support developers. Those context gaps during longer conversations also mean it is not quite at a perfect level yet.

I have been using Conversations by NLX for about a year and a half.

Conversations by NLX has been very stable overall. We rarely experience any downtime that impacts our users, and it handles traffic spikes quite well. The only minor hiccups we have seen are those occasional context retention issues.

Conversations by NLX handles scalability exceptionally well, which was one of the main reasons we chose it. Since it runs on public cloud infrastructure, it automatically adjusts to handle traffic spikes without any noticeable lag, ensuring a smooth experience for our users, no matter how many people are interacting with it at once. It also allows us to easily deploy new conversational flows.

The accuracy of Conversations by NLX is quite strong, particularly when it comes to understanding customer intent and providing relevant information. It is highly reliable for handling those repetitive tasks without drifting off-topic. However, there are occasional moments where it might struggle slightly to maintain context through a very extended, complex discussion, which is why we do not consider its reliability to be absolutely perfect, and sometimes it hallucinates.

From a security and governance perspective, Conversations by NLX holds up really well for enterprise use. Its compliance with major industry standards gives us peace of mind, and the management features allow for clear role-based access control.

We have generally seen wait times with Conversations by NLX cut by at least 17% to 20%. Our support team is handling roughly half as many routine tier-one tickets as they were before it. It really freed up a significant amount of their day.

I am not certain about the exact metrics regarding return on investment with Conversations by NLX because I am a developer and do not handle the return on investment or the payment levels.

Conversations by NLX is doing a great job and having a decent amount for the subscription. I think it is good. You can also have multiple offers, but I think it is a good and reasonable way.

Before deciding on Conversations by NLX, we did evaluate a few other options. We used Google Dialogflow and Amazon Lex to see how they compared in terms of multimodal capabilities and integration with our cloud infrastructure.

We were a startup company and wanted to try out a few tools that are available before switching to Conversations by NLX to get those advanced features, especially to handle more complex, context-aware interactions and to streamline our agent handoff process. We have not productionized it completely, but it is still in the POC level. We are seeing a good performance in Conversations by NLX. I have covered most of the features of Conversations by NLX and everything regarding other improvements Conversations by NLX needs. My overall review rating for Conversations by NLX is 8 out of 10.

I used Conversations by NLX once last year. The main use case for Conversations by NLX when I used it was to build a chatbot conversation bot for a BFSI client.

I built a chatbot wherein users, when called or using chat-based tools, get authenticated and raise queries such as raising a dispute regarding their balances, paying their account balances, or checking the account balances. The chatbot is an intelligent bot that gives users answers to their account balances after verification and asks them to pay the account balances immediately. If the balance is between $50 to $100, it provides one payment installment and a 10% instant discount. For $100 to $500, it offers four payment installments and a 12% discount, and it scales up to $10,000.

Conversations by NLX was pretty easy to use. The GUI was straightforward and anyone can use it without any prior knowledge. I am happy with it.

The best features Conversations by NLX offers are the NLP engine and the bot reading. What I appreciate most about the NLP and bot reading features is the bot training capabilities. I cannot compare it with any other tool currently, but it is straightforward and very easy to use, so I would rate it five out of five.

Conversations by NLX positively impacts my organization by helping in gathering customer inputs and providing resolution for their day-to-day conversations based on disputes, checking account balances, or paying account balances, thus reducing the average handling time. The average handling time was earlier around seven to nine minutes and has been reduced to five minutes.

One thing I would share regarding Conversations by NLX is the need to refine the self-service flows and integration capabilities for multi-modal usage and leveraging the analytics for personalization.

Regarding Conversations by NLX's AI capabilities, it has Intent automation that can trigger autonomous API calls. It can guarantee zero hallucination, prevent mixing topics, and wrap the conversation in a structured way.

For governance, I know it has RBAC (role-based access) and a virtual workspace. For security, it is compliant with data protection guardrails and enterprise-ready hosting, so it has all the security compatibilities required nowadays.

The accuracy and reliability of Conversations by NLX's output has core capabilities such as voice and multimodal AI, generative script workflow, and global reach. The output of the AI capabilities includes intent detection.

Conversations by NLX's intent detection and global reach has actionable outputs that can generate context-aware, cited references and can highlight information from large document sets, such as manuals or technical documents, directly to users.

The areas of capability improvement for Conversations by NLX are agentic AI and task automation, multi-modal UI, and intent classifications. These areas of improvement would enhance the voice and technology, expand the platform's ability to handle complex multi-step native calls, and expand support beyond native languages to add more languages.

Conversations by NLX is stable.

Conversations by NLX's scalability is pretty much scalable. It has a lot of speed to scale and can be scaled based on the number of chats or conversations it can handle. It has a seamless integration plugin to enterprise architecture such as Lex, Bedrock, or Contact Lens without disrupting existing backend solutions. This demonstrates the scalability of Conversations by NLX and it is beneficial that it can scale on its own based on requirements.

I do not require customer support for Conversations by NLX currently, but if I do require it or find out about the customer support in the future, I will definitely provide feedback.

I previously used Unifor for some clients and the Google Dialog bot with integration with Genesis. The choice depends on client requirements. All solutions are unique in their own ways and the selection would depend entirely on what the client's requirements are.

My experience with pricing, setup cost, and licensing for Conversations by NLX is that there is no upfront cost or setup cost. It has a feature-based pricing structure that begins with a free tier and scales depending on usage, whether they are using standard chat or multi-modal conversation. Depending on the capability being used, such as voice-plus technology, low code, omnichannel, or multi-language support, this is the best part of using Conversations by NLX and that is impressive.

AWS is used for deploying Conversations by NLX.

I have not seen a return on investment regarding Conversations by NLX yet. The client has not come back to me regarding the return on investment. However, it has definitely reduced the client's need to increase the headcount or the agent count after building the conversation AI tool or bot using Conversations by NLX analytics.

My experience with pricing, setup cost, and licensing for Conversations by NLX is that there is no upfront cost or setup cost. It has a feature-based pricing structure that begins with a free tier and scales depending on usage, whether they are using standard chat or multi-modal conversation. Depending on the capability being used, such as voice-plus technology, low code, omnichannel, or multi-language support, this is the best part of using Conversations by NLX and that is impressive.

I did not evaluate other options before choosing Conversations by NLX.

Conversations by NLX is designed for multimodal voice and digital self-service and can handle multilingual conversations. If they have similar usage, they can definitely consider Conversations by NLX because it can also leverage AI applications and you can bring your own LLM models to be used with Conversations by NLX. It can handle multilingual conversations in one frame of time and also has seamless channel deployment which can be tested in real time without wasting time or utilizing a native testing environment before going live. These are the tips and suggestions I would give to somebody considering using Conversations by NLX. I would rate this product a 7.5 out of 10.

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.

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.

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.

I have been working in my current field for the past 20 years.

Conversations by NLX is stable in my experience, though there is sometimes downtime or issues.

Conversations by NLX sometimes faces difficulties regarding scalability, though sometimes it performs fine.

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.

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.

My experience with pricing, setup cost, and licensing for Conversations by NLX seems fine.

Conversations by NLX is worthwhile. It is money-saving and time-saving as well.

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.

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.

I have been using Conversations by NLX professionally for four years.

The best features Conversations by NLX offers include flexibility and the ability to loop back to the main question. I appreciate that it asks, "Is there anything else I can do for you?" so I do not need to initiate the same conversation again and go through the same flow because, as a user, I do not know the flow. If it helps me go back to previous stages of the conversation, that helps significantly, whereas a one-directional path makes it really hard for users to navigate.

Conversations by NLX positively impacts my organization by using an LLM to help us develop this type of tooling. However, I feel that it is also pushing the problem forward. Implementation is cheap, but review and quality are expensive. Thus, it pushes the problem to a further stage of the standard development cycle.

Improvements for Conversations by NLX can be made by focusing on context. The more data you push, the more personalized and problem-solving it becomes. For instance, using the phone assistant starts with a zero stage, knowing only my phone number, but it should also save some data. When starting the conversation, I expect this assistant to already know things about me. Data protection rules exist, but I want to feed it as much information as possible so the conversation flows better. It should at least know my job, name, age, and perhaps previous history of conversations, so I do not have to explain the whole history repeatedly.

For the fintech, I have been working for six months, and for the healthcare, it was around four years.

In my experience, Conversations by NLX is not stable, and I have not used it.

I have not switched from a different solution before this; I am still using the old one.

Regarding outcomes from Conversations by NLX, the implementation is probably cheaper, around fifty to sixty percent for many companies using this type of practice. This allows us to bring new tooling to the market faster and experiment quicker. In one day, during a hackathon, we can do a lot and showcase it. However, while this implementation saves time, it has pushed the quality issue forward. Making it production-ready becomes harder because dumping a lot of code does not necessarily speed up the job. Many people can work on languages and systems they do not know, allowing them to learn and implement faster, but I would still be cautious about the end stage, which is quality.

I have not seen a return on investment with similar systems since I found that usually the application and user experience are better rather than saving time or money.

Before choosing Conversations by NLX or similar systems, I did evaluate options, including a German company.

My main use case for Conversations by NLX is building one, and I am also a user of the same application, which is called the phone assistant by Doctorlib.

I use Conversations by NLX to communicate with my doctor's practice by calling the practice, where an AI phone assistant picks it up and asks what I need. I explain my needs, and then it goes into one of the flows such as appointment booking or prescription, and I can automatically book an appointment on the phone without using anything else.

As a user, it feels as though Conversations by NLX is trying to be smart, but it is sometimes hard, and I might need human interaction for this type of thing, especially for healthcare. When it involves something personal, I would prefer to have a personal human touch. AI systems are getting better and more personal, but some users still do not prefer talking to an AI system at all.

My application was a phone one, but Conversations by NLX can also be adapted to a web application. Usually, it is a chat interface to talk through, but I think it needs a revamp of how we interact with Conversations by NLX systems. I prefer it to be all the way through a phone call, not a chat interface because I do not want to write; I just want to talk or visualize it rather than reading the whole text.

Concerning Conversations by NLX's AI capabilities, governance and security are significant topics. Data can be shared, but it all goes back to security. Securing the models and having guardrails is really important because input and security posture are crucial regarding the attack surface. The attack surface is extensive, as it only accepts text and can do anything with it. Therefore, you need to control what you are feeding it and limit its access and manipulations.

My advice for others looking into using Conversations by NLX is simple: try it. It is not complicated. I would rate this review nine out of ten.

We're using Conversations by NLX or the ACXD platform with AWS to bring to life AI agents and deterministic bot flows into the contact center for our customers.

We created a demo with Conversations by NLX to provide customers an overview of how the Live Sync feature with ACXD can be brought into the customer's requirements and their current customer flows to show them how the tool works and exactly how we can build it out for them.

Our other use case for Conversations by NLX is to provide customers a faster delivery time for their migrations into the Amazon Connect platform. The ACXD tool, which is Conversations by NLX, helps customers deliver quickly and design and deploy quickly customer interactions using voice bots, chatbots, and other solutions.

The best features Conversations by NLX offers include the guided flow bot diagram where you can use blocks and tools to connect into the Amazon Connect customer tool. Additionally, Live Sync is an excellent tool and a module that you can bring in to help bring voice to life for your customers so that if they're on a website, the AI agent can actually perform actions on the website for that customer without them having to click themselves. It helps them drive the interaction utilizing AI agents through ACXD.

My customers are responding very positively toward the features of Conversations by NLX. It is a state-of-the-art tool with features that no other competitor has and definitely something that leaves them impressed after viewing the demos.

Once Conversations by NLX brings it into the Amazon Connect customer UI, there will be a huge improvement right away. That's the biggest improvement.

Regarding Conversations by NLX's AI capabilities, its governance and security are very highly regulated. One thing that could be added in the future is programmatic access into the tool as well as some IaC options.

I have been using Conversations by NLX for the past couple of months since it has been in the private preview with AWS.

Conversations by NLX is going to help us deliver our opportunities much quicker than we used to. Prior to that, building out flows and bots using Amazon Connect and Amazon Lex usually took longer to deliver. Now we will be able to speed up that process considerably.

While I do not have exact numbers or metrics for Conversations by NLX, it is absolutely reducing the time to delivery. AWS and Conversations by NLX have provided some metrics, one of which is United Airlines where they were looking at a 12-month deployment time and using ACXD, formerly Conversations by NLX, shortened that down to three months.

Regarding Conversations by NLX's AI capabilities, it uses Amazon Lex in the background, so it has a high accuracy on output, very similar to what customers get today with Amazon Connect.

We use a variety of different models for deploying Conversations by NLX. We have public and private clouds and are utilizing the ACXD, formerly Conversations by NLX, in our private preview to give our customers experiences and learn how it can help them deploy faster and migrate faster within their environments.

We did not purchase Conversations by NLX through the AWS Marketplace. We are a partner of Amazon Web Services and we are a part of the private preview to help our customers migrate to ACXD.

Conversations by NLX is an exciting platform being brought into Amazon Connect and the additional charges will be part of the unlimited AI. There are no heavy fees added onto it like there are with other AI agent tools. It is absolutely a great product at a low price.

I rate Conversations by NLX a 10 out of 10 because it is better than any other AI agent tool that I have used on the market so far.

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.

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.

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.

I have not used Conversations by NLX in the production environment, but I have used it for proof of concept projects for three different customers in the UAT environment for the last six months. The main use case is for conversational AI where the call comes to our call routing solution, and from there, it gets transferred to Conversations by NLX to provide intelligent IVR treatment for customers. Conversations by NLX performs intent classification based on what the customer is saying, automatic speech recognition, and text-to-speech. It also conducts account lookup based on customer-provided information. A small amount of LLM or AI usage helps with better intent classification and FAQs. Once Conversations by NLX completes its processing, if it cannot solve the customer's issues, the call comes back to our call routing solution. Conversations by NLX also provides the most appropriate queue to which the call should be routed based on the current status of the account, and using that information, our call routing solution sends the call to that agent or queue.

What I like the most about Conversations by NLX is that the contact center industry, especially the legacy contact center industry, is very much accustomed to and comfortable using drag-and-drop blocks, connecting them, and writing the required business or application logic to serve business requirements. Conversations by NLX provides the same kind of web-based studio where you drag and drop blocks, connect them, and wherever required, you write business logic primarily using JavaScript. The studio is not only a place to develop your solution but also acts as a graphical representation of the overall solution. This is the first thing I appreciate about it, and it is what our customers appreciate about it, especially when compared with Amazon Lex, where they still have a graphical representation of things but not as comprehensive or anywhere close to Conversations by NLX.

The cost per call or per minute is relatively less. I cannot definitively compare it with the other two products that I have closely worked with, but the cost is relatively less compared to a couple of other competitors of Conversations by NLX that I worked with. The amount of coding required is less compared to other solutions, and while it still requires some amount of coding, it is relatively less when compared with other competitors. Integrating or building AI solutions or AI agents through Conversations by NLX is also easier compared to other competitors. These are the top four things that I appreciate or my customers appreciate about it.

I was not able to get approval to implement Conversations by NLX to more customers and business units because the cost is still high, especially when LLMs or AI get involved. That is one challenge regarding cost. Secondly, there are over half a dozen conversational AI providers who are doing exceptionally well in the US market as well as the Europe market. It is very competitive, so Conversations by NLX has to do a lot better, especially as I have difficulties promoting Conversations by NLX to some parts of European countries like Greece, Poland, and Austria. When it comes to European languages, they have to do a lot better. They are doing great with US English and Spanish, but compared with that part of Europe, it is a problem. Thirdly, it is hard for customers to open an account on the nlx.ai website and start building use cases. When I take Amazon or Google, it is relatively easy to create a contact center instance or conversational AI instance and start building use cases. Those kinds of things are not there in Conversations by NLX. I am also unable to reach NLX support to find answers for those things. Fourthly, since it has been acquired by Amazon, access to any new customers is completely blocked, and as of this month, it is simply not available since for the last several weeks. That is another big disadvantage.

I have been using Conversations by NLX for over six months.

Regarding stability, I would rate it ten out of ten.

For scalability, I would also rate it ten out of ten.

If you are a registered customer and need technical support regarding Conversations by NLX, it is easy. It is just that if someone is a random person trying to access nlx.ai to look around for training or access, technical support is not good. For registered customers, getting technical support is very easy. I would give a score of nine to the support on a scale from one to ten.

When I first started using Conversations by NLX, it was relatively easy for me to set up because I have worked on similar products such as Amazon Lex and Amelia. However, for any new customer, it is still difficult without proper training. Not just Conversations by NLX, if the customer is totally new to the conversational AI world, it is not easy. Much more training and access to build things for a reasonable cost is required.

Compared to other conversational AI solutions, Conversations by NLX requires very little maintenance. Once you are done building it, things like automatic speech recognition and text-to-speech going down or any latency issues are extremely rare. With that said, maintenance is relatively very little. I would give this review a rating of nine out of ten overall.

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.

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.

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.

I have been using Conversations by NLX for almost a year.

Conversations by NLX is stable.

Conversations by NLX's scalability is pretty good, and they are very scalable.

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.

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.

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.

My company does not have a business relationship with Conversations by NLX other than being a customer; there is no relationship.

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.

The pricing and implementation details of Conversations by NLX are not fully transparent upfront, so evaluation may require a sales conversation.

Before choosing Conversations by NLX, I evaluated other options, and we evaluated many different options, even including Perplexity and Copilot.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

I have been using Conversations by NLX for the last year.

My main use case for Conversations by NLX is in a chatbot. I was creating an AI-based, LLM-based app where I used Conversations by NLX, NLP, and NLU.

I used these tools in my Sparkathon project, which was a hackathon project and an internal AI event that I participated in. I created an NLX-based LLM app for this event.

I was able to use Conversations by NLX smoothly. It was a very good experience.

In my opinion, the best feature Conversations by NLX offers is natural language processing. Whatever language you are using, whether it is Hindi, English, or any other language, it will convert it accurately, letting you feel as though you are talking to a human. That is the best part I have seen.

Conversations by NLX has positively impacted my organization as they are effectively using it. My company uses it almost every day, mainly because my company focuses on chatbots.

Since using Conversations by NLX, I have noticed specific outcomes and benefits. It has effectively improved customer satisfaction, reduced time spent on tasks, and reduced costs. In every aspect, whether it is customer satisfaction, saving time, or reducing costs, Conversations by NLX has been helpful. I am progressing with it every day.

We are already working on how Conversations by NLX can be improved. Every day we are learning, and it is the way we work every day. Just as LLM works by training, we are using Conversations by NLX and we are learning from it.

I do not have any additional improvements needed for Conversations by NLX to mention.

I have been working in my current field for three years.

Conversations by NLX is stable.

Conversations by NLX's scalability is good. You can scale it according to your needs.

Customer support for Conversations by NLX is good, and I would rate them 10 out of 10.

I never used a different solution before Conversations by NLX.

I cannot share any return on investment because I am not aware of the money metrics.

Regarding my experience with pricing, setup cost, and licensing, I am not certain about that because other teams take care of it.

I did not evaluate other options before choosing Conversations by NLX.

Conversations by NLX's AI capabilities are based on governance compliance. It helps customers and organizations secure their interactions, whether it is chat, voice, audio, or video.

Conversations by NLX's accuracy and reliability of output is very good. I have observed almost 99.99% accuracy.

I would recommend everyone use Conversations by NLX and give it a try to see how the experience is. I would rate this product 9 out of 10.