Botario

Through role-based rights management, users can be flexibly added and managed. From technically experienced users to inexperienced users from specific departments, you can assign different roles and rights to users.

With botario, content can be edited and expanded quickly and easily by simply entering content examples. You can either enter intents directly, transfer them from dialogs or have them created automatically with the content generator. Entities are created automatically by the content generator and the convenient botario entity annotator is used for manually entered entities.

Set any sequence of responses and actions in response to user interaction. The reaction of the chatbot can be split into several text bubbles and can contain buttons, links or media. botario can randomly choose between different defined response variants to create an individual and unique user experience. With an action script you can address external services before and after responses and have calculations performed based on tracked data. If the chatbot is not sure which answer might match the user input, an automatic fallback action can be triggered. The fallback action asks the user to specify his request and the tracked data is reset to the state before the last answer.

Create dialogs simply by drag & drop. Define start, intermediate and end points. On this basis botario learns which actions or responses should follow which inputs and dialog progressions. Create a reliable user experience and greater robustness thanks to flexible dialog trees with artificial intelligence.

You can customize botario according to your requirements. With botario you get all the liberties of the Rasa stack and you can design the user interface according to your wishes. You can also customize functions or create your own actions and interactions with external systems.

With botario you are completely free to choose and configure the machine learning models and AI components. In addition to ready-made standard models, you can also use model components that you have configured yourself. botario offers Rasa standard pipelines as well as custom pipelines developed in-house.

With automated tests for your created examples including error logging and visualizations you get a reliable quality control of your chatbot. If errors occur during the test of the Natural Language Understanding (NLU) components used, they are logged exactly and can be easily corrected afterwards. All NLU components used are regularly adapted and supplemented to the current state of AI research. You can also easily integrate your own or external NLU components into botario.

The chatbot is able to speak numerous languages. Depending on the language, you can use pre-trained models and have your own content automatically trained, so that specific technical terms and jargon can also be processed without difficulty.