Kore.ai Experience Optimization (XO) Platform is a conversational AI platform for enterprises that automates and optimizes CX and EX. The platform includes tools to design, test, train, deploy, analyze, and manage Intelligent Virtual Assistants.
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Rasa
Score 6.0 out of 10
Enterprise companies (1,001+ employees)
Rasa is a conversational AI platform from the company of the same name headquartered in San Francisco, enabling enterprises to build customer experiences. Rasa’s platform was built to create enterprise-grade virtual assistants, allowing personalized conversations with customers - at scale. Rasa’s conversational AI platform allows companies to build better customer experiences by lowering costs through automation, improving customer satisfaction, and providing a scalable way to gather customer…
It is a very flexible virtual assistance tool that is easy to develop enterprise-level complex bots without the knowledge of highly skilled programming. The platform has a straightforward and user-friendly interface. It has excellent documentation and answers all the possible questions of clients. Moreover, its customer support is really great. It is one of the fastest chatbot development platforms that are scalable, easy to integrate, and provides various domain support. Overall I had a great experience with Kore.ai.
I have been using the platform for over 3 years and I have noticed a very good evolution, in an attempt to reinvent themselves. The support team is amazing, always available to work out with us in achieving the best results. About the technology, the algorithms available in the platform suits most of the cases. Being language agnostic is a very positive point for us, because some big tech platforms have little support for PT-PT language.
Rasa CALM flows and Rasa domain could be made fully independent of the Rasa training process and dynamically retrievable from e.g. a graph DB. This would make the chatbot more flexible.
Prompt templates, or at least paths could be referenced in Rasa config. Different policies in the Rasa config could then be configured without code change to use different prompt templates
LLM configuration should rather be part of the endpoints, than model configuration.
Rasa Studio could support all the functionality of Rasa Pro.
For new users, it has one of the best UI/UX experiences. One can easily get used to the platform and integrate enterprise-level intelligent chatbots. It uses many AI algorithms that understand the queries very effectively and helps resolve client issues. You don't need any prior high-level experience in coding to build chatbots and can easily integrate a chatbot with the Kore.ai platform.
With the help of dedicated team - documentation and video resources it is relatively easier to build. We prioritized pro-code usage to begin with launch.
First of all, It has been great till now in my opinion. I have helped in building more than 10 chatbots using this platform and have not faced any major issues till now. It builds enterprise-level chatbots with just a little knowledge of coding. It is intelligent and answers all possible questions of clients. It needs just some minor fixes but overall it's superb.
Rasa support has been very responsive, trying to fix any reported issues ASAP. They've also listened to many requests for improvement. The Rasa features and changelog are well documented
Glean - proprietary semantic search algorithms, no backend actions integration IBM Watsonx - complicated dialogue builder, poor separation of no-code and pro-code interfaces ELMOS (agent based) - all logic in code, no dialogue logic in no-code interface possible Rasa - transparent and simple sharing of objects between no-code and pro-code interfaces. Transparent LLM usage and restrictions. Simple backend integration via Rasa SDK
