Certified enterprise ready
Scalable Open Source Chatbot Platform to build multiple Chatbots with NLP, Behavior Rules, API Connector, and Templating. Developed in Java, provided with Docker, orchestrated with Kubernetes or Openshift.
Enterprise-Ready Chatbot Platform for creating, running and maintaining customizable chatbots. Scales Out very well due to resource-oriented design & RESTful architecture. NLP Parser for matching user inputs as words and phrases even in case of spelling mistakes or missing spaces between words. Behavior Rules for making decisions with predefined and custom conditions.
Scales out horizontally
Horizontal scaling is supported through resource-oriented design & RESTful architecture, which also provides the ease to integrate and connect with other resources (API-Connector).
In-Memory NLP Parser
Match user inputs as words and phrases, even in case of spelling mistakes or missing spaces between words.
Flexible Behaviour Rules
Make decisions with predefined and custom conditions.
Store context information between user interactions in order to make better conversational decisions
Track all changes made to all configurations and use different versions of your configurations in different bots to allow multiple bots with shared knowledge.
Dynamically compose output from bots for the ease to quickly build your own templates.
Full Bi-Directional GIT Sync
Use init, commit, push and pull to integrate a Chatbot to a GIT repository of your choice.
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Read what others are saying about this product in our review section.
What do you like best?
Fast and reliable chatbot framework with an awesome parser. And any http interface can be implemented.
What do you dislike?
Documentation could be better, but it is getting better
Recommendations to others considering the product:
If you know just a little bit of development and you have a non standard chatbot project in mind, where more systems are involved, this is the framework
What problems are you solving with the product? What benefits have you realized?
Chatbot implementation can focus on the dialog and the integration of other services. The technical side is implemented, so chatbot development time is drastically reduced.