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    AI For Travel

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    Sold by: Kore.ai 
    Deployed on AWS
    Powered by Gen AI and Conversational AI, AI For Travel is a prebuilt suite of self service accelerators designed to transform travel experiences. With seamless integration into digital and voice channels, it enhances speed to market, boosts guest satisfaction, drives loyalty, and empowers employees. Leveraging Kore.ai AI for Service, AI for Work, and AI for Process, TravelAssist enables intelligent, real time conversations meeting travelers wherever they are in their journey.
    3.8

    Overview

    Unlock the power of AI to create exceptional travel experiences, optimize operations, and elevate customer satisfaction. TravelAssist is designed to enhance every touchpoint in the travel journey delivering intelligent automation, hyper-personalization, and seamless omnichannel engagement.

    Leveraging advanced Generative AI and Conversational AI capabilities, Travel Assist enables seamless interactions through intelligent virtual assistants (IVAs) and process bots that can be deployed across your digital, voice and social media channels, ensuring your customers receive hyper personalized assistance anytime, anywhere.

    Enterprise-Grade AI Integrations, Leverage industry-leading LLMs like Amazon Bedrock and Anthropic for unparalleled conversational intelligence.

    Next Level NLP Accuracy Experience improved, intent detection for faster, more precise customer interactions.

    Trusted Generative AI Responses, Deliver reliable, knowledge driven answers by tapping into trusted data sources, ensuring accuracy and compliance.

    Omnichannel, Effortless Engagement, Deploy AI powered interactions across multiple channels with single flow multichannel deployment.

    Customizable Self Service Experiences, Offer tailored voice, chat, and multimodal solutions that enhance customer autonomy while reducing support costs.

    Hyper Personalized Conversations, AI driven insights create uniquely engaging interactions, fostering deeper customer connections and brand loyalty.

    No Code, AI Powered XO Platform, Quickly design dynamic, human like conversations with generative AI, making automation effortless.

    Whether its streamlining bookings, assisting with travel disruptions, or enhancing employee workflows, TravelAssist redefines efficiency and engagement in the travel industry. Future proof your operations and elevate customer experiences start your AI transformation today.

    Highlights

    • Trusted Generative AI Responses, Deliver reliable, knowledge driven answers by tapping into trusted data sources, ensuring accuracy and compliance
    • Customizable Self Service Experiences, Offer tailored voice, chat, and multimodal solutions that enhance customer autonomy while reducing support costs
    • No Code, AI Powered XO Platform, Quickly design dynamic, human like conversations with generative AI, making automation effortless

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    Deployed on AWS
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    1-month contract (12)

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    Dimension
    Description
    Cost/month
    Digital 1k pm
    TravelAssist(Digital) - 1,000 Sessions per month + Standard Support
    $350.00
    Digital 2.5k pm
    TravelAssist(Digital) - 2,500 Sessions per month + Standard Support
    $875.00
    Digital 5k pm
    TravelAssist(Digital) - 5,000 Sessions per month + Standard Support
    $1,750.00
    Digital 10k pm
    TravelAssist(Digital) - 10,000 Sessions per month + Standard Support
    $3,500.00
    Digital 25k pm
    TravelAssist(Digital) - 25,000 Sessions per month + Standard Support
    $8,750.00
    Digital 50k pm
    TravelAssist(Digital) - 50,000 Sessions per month + Standard Support
    $17,500.00
    Digital and Voice 1k pm
    TravelAssist(Digital+Voice) - 1,000 Sessions per month + Standard Support
    $365.00
    Digital and Voice 2.5k pm
    TravelAssist(Digital+Voice) - 2,500 Sessions per month + Standard Support
    $913.00
    Digital and Voice 5k pm
    TravelAssist(Digital+Voice) - 5,000 Sessions per month + Standard Support
    $1,825.00
    Digital and Voice 10k pm
    TravelAssist(Digital+Voice) - 10,000 Sessions per month + Standard Support
    $3,650.00

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    Software as a Service (SaaS)

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    Support

    Vendor support

    As part of our support services, we resolve customer queries quickly, efficiently and cost effectively using our highly skilled support team. Our support team will identify your problem and come up with a solution promptly. We provide 24/7 support as per agreed SLAs with the client

    https://kore.ai/contact-us/ 

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    Customer reviews

    Ratings and reviews

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    3.8
    4 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
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    2 AWS reviews
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    2 external reviews
    External reviews are from PeerSpot .
    Farheen Mulla

    Dashboards have transformed policy audit visibility but voice chat capabilities still need exploration

    Reviewed on Apr 19, 2026
    Review provided by PeerSpot

    What is our primary use case?

    I used Kore.ai  to make dashboards, widget creation, and I tagged some columns. I wanted to create dashboards to get all the details for policy, specifically to understand who are the legacy policy users and who are the Guidewire policy users.

    The widget in our system was for the policy product. In that product, users were not able to see on a page how many users logged in today, whether a legacy person or Guidewire user logged in, or what changes or modifications they made. I created dashboard widgets so that legacy users and Guidewire users could track the changes they made in their policies.

    I used Kore.ai  for this purpose. Before that, I migrated from Kore.ai 10 to 11. I trained the model by adding utterances as training data and achieved almost 97% accuracy. After that, I started working on widget creation.

    What is most valuable?

    The best feature I have worked on is widget creation. I went through the entire chatbot workflow to create it, so I have a good understanding of that part. I appreciate the process of adding tags and fetching data by creating a dashboard.

    For the admin side, they will get an audit that shows who logged in—legacy or Guidewire users—and what modifications they made. This helps them by seeing that dashboard rather than viewing each policy individually.

    It impacted my organization by helping us move into being AI-native. Our organization is proving themselves that they are AI-native, and it helped a lot to show other clients that we have worked in AI.

    What needs improvement?

    I have worked only for six months on Kore.ai. While working on it, I haven't seen any area that needs improvement because I need to explore more in voice chat. I don't think there may be any improvement needed for that part as of my knowledge.

    I want to work on voice AI chat, but I have not yet been involved in that. For that project, I was working on widget creation, training the model, and migrating from Kore.ai 10 to 11. Then I moved to a different project, so I couldn't explore that. This is a regret for me. In the future, if I get an opportunity with Kore.ai, I will definitely work on voice AI chat.

    For how long have I used the solution?

    I have used Kore.ai for six months.

    What do I think about the stability of the solution?

    Kore.ai is stable.

    What do I think about the scalability of the solution?

    Kore.ai is a scalable product. I think they can add more features, but right now I'm unable to recall something specific for improvement. Definitely, it's a scalable product.

    How are customer service and support?

    The customer support was good. We connected two or three times and received full support from the customer support team.

    Which solution did I use previously and why did I switch?

    I haven't switched to any other solution. I got Kore.ai first and worked on that only. It is a good product.

    What was our ROI?

    It is definitely a money saver and time saver.

    Which other solutions did I evaluate?

    I haven't evaluated other tools. Kore.ai was the first one, so our organization went with it.

    What other advice do I have?

    For the process of adding tags and fetching data for dashboards on the admin side, admins will get an audit that shows who logged in—legacy or Guidewire users—and what modifications they made. This will help them by seeing that dashboard rather than viewing each policy individually.

    I give a nine for the customer support. I will recommend Kore.ai to others. If anyone is looking for tools similar to Kore.ai, I will definitely recommend it. I will recommend it to someone if they are having issues or problems with other tools. I definitely want to explore more of this product. I gave this review a rating of seven.

    Judin Augustin

    Automation has reduced large call centers and provides real-time outbound support for patients

    Reviewed on Apr 17, 2026
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Kore.ai was creating an outbound calling generative AI-powered chatbot, which is useful for insurance and healthcare companies.

    What is most valuable?

    Kore.ai is a low-code platform, and you do not necessarily have to be an expert in artificial intelligence or generative AI to use this platform. However, if you have that experience, it will be a valuable add-on. The main advantage is that it has almost every kind of plugin available to use, whether for live agents or if you want to use it as a call center. You have real-time capabilities and the most useful plugins available, with almost every kind of model available with configurations. We can configure the ML models and train them. The platform is very user-friendly with explanatory features and a great UI.

    One significant feature is the live testing platform with Kore.ai. When you are creating a workflow, you have an interactive, real-time testing platform that reflects every change you make. This makes it easy to debug errors or add new features. Additionally, Kore.ai has many different tools and platforms that cater to different needs, whether for a call center, normal workflow, or machine learning workflow, which is really useful.

    Because of Kore.ai, it was much easier than creating something manually. A low-code platform always helps, and when that platform has this much capability, it provides far more value than manual development. It was particularly helpful for our team that we could create a POC and get that project into production. Kore.ai helped our team build a generative AI outbound calling chatbot, and it truly helped our customers.

    If you have a hospital with a thousand employees in a call center, you might consider outsourcing. However, with Kore.ai's outbound calling capabilities, you can eliminate the outsourcing part. You do not need a thousand call center employees. You can accomplish this through automation with just one or two employees if people need to switch to agents. This represented a significant cost reduction.

    What needs improvement?

    Kore.ai can be improved by enhancing their documentation, which is currently a bit disorganized. They should include detailed videos or workshops. There are not many videos or community resources available, so adding more would be beneficial.

    Integrations with real-time models with Kore.ai would be great. Advanced models like Claude or Anthropic models would be valuable additions.

    Regarding the rating of 8 instead of 10, the missing comprehensive documentation, tutorial videos, workshops, and community services are factors that reduced the score. Additionally, the unavailability of real-time advanced models from Anthropic or Grok also contributed to deducting one point.

    For how long have I used the solution?

    I have been using Kore.ai for nearly one and a half years.

    What do I think about the scalability of the solution?

    Kore.ai's scalability is pretty much scalable both vertically and horizontally.

    How are customer service and support?

    The customer support is top-notch, and they respond promptly. I have been in direct contact with the team, and they typically reply with respect.

    Which solution did I use previously and why did I switch?

    We used different solutions, including manual calling.

    What about the implementation team?

    For my project or workflow, I collaborated directly with the Kore.ai team. It was an intra-team project, and it was really useful that their UI was very well-designed so that you do not necessarily have to go to the documentation to find anything. You can look at the name of the icons and understand what they do. For my workflow, I had to connect this with a live call center system. There were plugins that helped me dial and call real customers. The plugins available were really good and useful.

    What was our ROI?

    As I mentioned, if you have a call center for 1,000 people, you can reduce that to two.

    What's my experience with pricing, setup cost, and licensing?

    My experience with pricing, setup cost, and licensing is comparatively lower than other companies and tools available.

    Which other solutions did I evaluate?

    We evaluated other options like Emma and Elsa, as well as other platforms, Python-based automations, and n8n-based automations.

    What other advice do I have?

    Really refine your use case, gather your requirements, and talk with the team to confirm if that is something possible before proceeding. I rated this solution an 8 out of 10.

    SumitSingh2

    Chatbot design has streamlined aviation and HR support but still needs better speed and cloning

    Reviewed on Apr 16, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for Kore.ai  is to design chatbots for customers in the aviation domain.

    I have developed one chatbot where we take reviews from customers, specifically customer satisfaction reviews from the airlines domain. Customers use our airlines and we measure the satisfaction rate from our services. We have developed the chatbot to review customer feedback.

    I have used Kore.ai  in multiple ways. I have developed a chatbot designed for HR, allowing HR to provide all information related to company policies and company information. Employees can ask about leave and company policies. New users can also get information about the company. We have developed an HR chatbot.

    What is most valuable?

    Kore.ai offers multiple support and services, including API integration, webhook integration, and multiple channels. These features allow you to integrate and use them very easily, and the documentation provided is excellent so you can reference it.

    The most valuable features in my day-to-day work are API integration and channel integration. I have mostly used the web channels.

    Kore.ai has impacted my organization positively by providing substantial support related to design and implementation. You can build your own logic and implement it using languages, such as Node. It provides a positive approach where you can design and implement your requirements.

    Since using Kore.ai, I have seen multiple improvements. I have used multiple platforms, including LivePerson  and LUIS, and Kore.ai provides considerable support for implementation. You can design your own layout very easily, integrate that, and easily integrate with multiple channels and webhooks. It is easy to deploy, and it can track any errors that occur, making it a good way to start with and easy to learn.

    What needs improvement?

    I have already seen Kore.ai implement the LLM, and I think there could be improvements with a few cloning properties. For example, if we can integrate with multiple channels, I suggest the ability to use cloning properties in scenarios involving a customer satisfaction chatbot where, based on the requirement and multilingual abilities, we can use human-behavior characteristics where a human can pause and talk.

    I choose 7.5 out of 10 for Kore.ai because a few things already need to be improved, one of which I have mentioned. Kore.ai is continually improving their product day by day, but a few things are still missing, particularly related to performance speed.

    For how long have I used the solution?

    I have been working in my current field for almost four or more years.

    What do I think about the stability of the solution?

    I do not find anything challenging with Kore.ai, as I am mostly using the straightforward approach to implement my own requirements and address problems. Therefore, I do not require any add-on features.

    What do I think about the scalability of the solution?

    In terms of integration with existing systems or third-party tools, I have faced challenges a few times, but mostly I have used straightforward methods to integrate channels easily. My role is basically to integrate multiple channels very easily, as Kore.ai provides most channels in their own marketplace and categories.

    How are customer service and support?

    I have a direct relationship with Kore.ai team and we have a direct connection with them, not through any marketplace.

    Which solution did I use previously and why did I switch?

    Since using Kore.ai, I have seen multiple improvements. I have used multiple platforms, including LivePerson  and LUIS, and Kore.ai provides considerable support for implementation. You can design your own layout very easily, integrate that, and easily integrate with multiple channels and webhooks. It is easy to deploy, and it can track any errors that occur, making it a good way to start with and easy to learn.

    How was the initial setup?

    New users can easily get started with Kore.ai by using it from the marketplace, as there are multiple marketplace applications that we have already designed and implemented.

    What about the implementation team?

    I am a partner with Kore.ai, as my company has a business relationship with this vendor beyond just being a customer.

    What was our ROI?

    Kore.ai is deployed in my organization as a private cloud, and we can use it for our own employees.

    What's my experience with pricing, setup cost, and licensing?

    I have designed, implemented, and developed 25 or more chatbots on it, and one of my chatbots is also placed on the marketplace in Kore.ai. I am also receiving compensation from Kore.ai, so I view everything positively.

    Which other solutions did I evaluate?

    Since using Kore.ai, I have seen multiple improvements. I have used multiple platforms, including LivePerson and LUIS, and Kore.ai provides considerable support for implementation.

    What other advice do I have?

    I would advise that Kore.ai is very useful for developing and designing chatbots for any related field, as things automate very easily using the channel integration and API calling.

    I find the documentation and resources provided by Kore.ai to be very useful. I have used them extensively, and they are very helpful, with proper examples and good clarification.

    I receive updates or new features from Kore.ai in my email since we have connected with Kore.ai directly. Each time, I receive an email, and I go to my platform to update it there.

    The community support or user forums for Kore.ai are very useful. Sometimes, when I face an issue, I go to the forum to ask a question, and they answer very easily and respond in a short timeframe.

    I rate this review a 7.5 out of 10.

    WaqasAmin

    Voice bots have transformed customer journeys but post-implementation support still needs work

    Reviewed on Apr 14, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use cases for Kore.ai  include a diversity spanning from banking and the BFSI sector, to the travel market including aviation, and applications on the automobile side. Kore.ai  has created sub-products for different industry verticals, which provides good use cases in terms of banking.

    A specific example of a use case in banking is where a client needs to perform real-time transactions from one account to another. I can call using Kore.ai, and as a consumer, I can transact an amount of dollars from one account to send to any beneficiary that is already added into my account. On the aviation side, we have done use cases with Riyadh Air, which is a new airline in the Middle East focused entirely on guest experience. Customers can call Riyadh Air help assistance to book a ticket, schedule a trip, or select seats at certain airports.

    I want to add the use of AI technology and the ASR and TTS services that we use as part of my main use cases. The performance of the bot becomes more dependent on what kind of external services or external LLM sources are being used. We are currently using Microsoft ASR and TTS services in most of the bots that we have deployed with Kore.ai, and Kore.ai has their inherent native Microsoft speech services enabled as well. Therefore, Kore.ai is more efficient when it comes to Microsoft ASR and TTS speech services. They have their own LLM, but based on our experience, we have used Cloud Anthropic most often and have also used OpenAI, which works very well with Kore.ai.

    What is most valuable?

    My favorite feature that Kore.ai offers is their Agent Desktop. If you are integrating Kore.ai with a contact center solution as an integrated solution, Kore.ai also provides a standalone solution. You can perform both types of deployment, and their Agent Desktop, Agent Assist, and Agent Co-pilot features are very exciting in terms of how they can pull in knowledge. They have their own knowledge libraries that can facilitate your agents when calls are routed from an AI agent to a human agent.

    The Agent Desktop and Agent Co-pilot become especially useful for my team when you have a large volume of knowledge to traverse through as a human agent. With Agent Co-pilot and Agent Assist inside the platform, the information from the knowledge base becomes easy for you to access. Based on customer intents during calls or chats, Kore.ai Agent Assist can detect the intents quite efficiently and bring out the best knowledge articles from the knowledge libraries to present to you as an agent. The system does most of the work that an agent has to do in finding knowledge and searching for it in real-time. We have improved the average handle time significantly with the use of Agent Co-pilot.

    Another exciting feature is the industry vertical-based bots that have already been tried and tested by Kore.ai. I don't believe any other vendor offers this with specific bots for the healthcare industry, aviation, BFSI, automobile, and insurance. They have predefined use cases already plugged in, so you don't have to start from scratch. Predefined templates inside the libraries can be reused and built upon for your bots.

    Kore.ai has positively impacted our organization by helping us roll out the platform in one of our Middle Eastern markets first, where Arabic language was a challenge. We addressed those challenges through our own local native Arabic speaking personnel and then moved to the European market, where there is significant language diversity. The more exposure Kore.ai received with us, the same kind of efficiency we achieved when switching from one language to another. We have built a team of 30 plus agents who are conversation designers, AI engineers, AI implementation engineers, and Kore.ai experts on the platform. Organizationally, we have progressed considerably with Kore.ai.

    The positive impacts we have seen include expected reductions in average handle time, which is typically around 40 to 50 percent for any BFSI industry use case. In automobile and aviation, the AHT reduction comes at a cost because the calls are longer. We track parameters such as AHT, customer experience, and CSAT. For example, how the bot engages with the customer, carefully takes the intents from the client, and then responds back to them reflects these metrics. We see KPIs related to average handle time and agent reduction playing a significant role as we are the biggest BPO provider.

    What needs improvement?

    There are some technological gaps with Kore.ai when it comes to language detection because this problem is common among all conversational AI vendors. They are using external sources for automatic speech recognition and generating text-to-speech services. The speech recognition mechanism remains primary for these vendors, including Kore.ai. We have also observed some limitations in scalability, particularly on Azure , where we have had to scale it on different cloud platforms around the globe. Implementing Kore.ai on Azure  microservices might be a challenge compared to what we have seen in AWS , where cloud services are easier to maintain.

    From the perspective of post-implementation support, Kore.ai can improve significantly because I have seen it lagging in their industry vertical. Other vendors are quite effective at providing post-sales support, and that is an area where Kore.ai can gain market traction through improvements.

    For how long have I used the solution?

    I have been using Kore.ai for more than five years.

    What do I think about the stability of the solution?

    Kore.ai is definitely stable. The on-premises version is the most stable, followed by the hybrid cloud model, and the public cloud setup is stable as well.

    What do I think about the scalability of the solution?

    Kore.ai's scalability has limitations, particularly on Azure cloud, which is not cloud dependent. It is mostly cloud agnostic, and while it scales very well with AWS , there are certain microservices on Azure that need elasticity, indicating gaps from the cloud provider, not from Kore.ai technology itself.

    How are customer service and support?

    Customer support is where Kore.ai has significant room for improvement. Post-implementation support is a particularly discouraging aspect for me.

    Which solution did I use previously and why did I switch?

    Previously, we have partnered with Cognigy and have our own in-house solutions, including Unify  apps. While other vendors have their positives and negatives, we prefer Kore.ai due to our strategic partnership with them, making it our go-to solution in the market. We worked with Cognigy previously, which is now acquired by Nice, and we specifically compared Kore.ai with Cognigy.

    What was our ROI?

    Definitely, we consider the digital transformation journeys for customers, taking into account that investment costs are typically higher in the first two years for implementing technology, identifying use cases, and mapping them. Once up and running, the benefits of AI come into play. The results we see are agent reductions of 15 to 20 percent in multiple cases, lower telephonic costs due to SIP provisioning, and improved customer experiences with voice bots, chatbots, and reduced call times.

    What's my experience with pricing, setup cost, and licensing?

    Licensing is worked out on a case-by-case basis with their account management teams based on volumes. Their expert app services, which provide professional support during implementation, are higher in price. We have an in-house team capable of implementing Kore.ai, but post-implementation support, as I reiterated earlier, needs improvement both in terms of cost and delivery.

    What other advice do I have?

    Teleperformance is an exceptional reseller from Kore's side, and we have a great partnership with them. We are direct vendors and resellers of Kore.ai as a direct vendor. For our public cloud deployments, we use AWS most often. We deploy Kore.ai using multiple configurations, mostly public cloud in AWS Frankfurt, Microsoft Azure in UAE, and we also have one on-premises deployment for one of the leading banks in the Middle East, so it is a blend of all. From the perspective of post-implementation support, Kore.ai can improve significantly because I have seen it lagging in their industry vertical. Other vendors are quite effective at providing post-sales support, and that is an area where Kore.ai can gain market traction through improvements. Another exciting feature is the industry vertical-based bots that have already been tried and tested by Kore.ai. I don't believe any other vendor offers this with specific bots for the healthcare industry, aviation, BFSI, automobile, and insurance. They have predefined use cases already plugged in, so you don't have to start from scratch. Predefined templates inside the libraries can be reused and built upon for your bots. I rate this review overall as a seven.

    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)
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