Software Engineer at a consultancy with 10,001+ employees
Real User
Top 5
May 4, 2026
I develop chatbots using Kore.ai. I developed a travel assistant using Kore.ai that books tickets, cancels tickets, or modifies journeys. I also integrate API data in Kore.ai so that it can fetch data from the API and display it directly to users.
Principal Solution Architect In Ai Space at a manufacturing company with 10,001+ employees
Real User
Top 20
May 3, 2026
The main use case for Kore.ai was building a chatbot for one of our insurance clients who required a chatbot to allow agents to directly ask about documents uploaded for verification. The chatbot checks if documents exist at a particular link that contains the personal documents of clients and then sends the status back to users or agents. If the document is present, agents may request to read it and check if certain conditions are fulfilled in the document. This is essentially a document validation agent created using Kore.ai as the front end, coupled with Teams channels for the agents. Kore.ai helped our team specifically in building the document validation chatbot by serving as the front end of the entire development. Using Kore.ai, we connected with the Teams channel and leveraged features such as API connections and API calls to easily retrieve the status of documents.
Senior Solutions Consultant at a tech services company with 501-1,000 employees
Real User
Top 5
Apr 14, 2026
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.
Kore.ai provides advanced tools like Agent Desktop and Agent Co-pilot, designed to handle vast data volumes and improve efficiency. The platform integrates seamlessly with APIs and channels, supports multi-language capabilities, and offers real-time testing.Kore.ai offers robust solutions for sectors like healthcare and aviation, enabling efficient ML model configuration and generative AI chatbot development. While there's room for improvement in language detection and scalability,...
I develop chatbots using Kore.ai. I developed a travel assistant using Kore.ai that books tickets, cancels tickets, or modifies journeys. I also integrate API data in Kore.ai so that it can fetch data from the API and display it directly to users.
The main use case for Kore.ai was building a chatbot for one of our insurance clients who required a chatbot to allow agents to directly ask about documents uploaded for verification. The chatbot checks if documents exist at a particular link that contains the personal documents of clients and then sends the status back to users or agents. If the document is present, agents may request to read it and check if certain conditions are fulfilled in the document. This is essentially a document validation agent created using Kore.ai as the front end, coupled with Teams channels for the agents. Kore.ai helped our team specifically in building the document validation chatbot by serving as the front end of the entire development. Using Kore.ai, we connected with the Teams channel and leveraged features such as API connections and API calls to easily retrieve the status of documents.
My main use case for Kore.ai was creating an outbound calling generative AI-powered chatbot, which is useful for insurance and healthcare companies.
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.