Updated tutorial: Database-driven chatbot

If you want to build a chatbot that gets its content from a database, there is a good news. The existing tutorial “Build a database-driven Slackbot” was just updated to adapt to latest features of IBM Watson Assistant. First, define a skill that reaches out to a database service like Db2. Thereafter, use the built-in integrations to easily tie in the assistant with Slack, Facebook Messenger, embed the chatbot into your own application or use the WordPress plugin.

Architecture of database-driven chatbot

Database-driven chatbot

With the acceptance of chatbots to supports business tasks and assist in enterprise workflows, it is critical to access systems of record from within a dialog. The tutorial shows how to build a database-driven chatbot and integrate it with Slack as user interface. Instead of Slack, you can also use the Assistant-provided preview, Facebook Messenger integration or WordPress plugin as alternative user interfaces. Dialog actions, realized as IBM Cloud Functions, query a Db2 or PostgreSQL database or insert new records. Therefore, a messenger application can serve dynamic, user-specific content from a database.

Conclusions

It is easy to build a database-driven chatbot. Reach out to systems of record from within a dialog, so that Slack or other messenging systems can support enterprise workflows. The updated tutorial all information to get started.
If you have feedback, suggestions, or questions about this post, please reach out to me on Twitter (@data_henrik) or LinkedIn.