Hello ChatGPT. I am building an inference engine and chatbot which I want to train on two datasets, one made of thousands of Azure Devops completed (meaning resolved) bug workitems complete with discussion by users and thousands of natural language messages posted on the engineering related Slack channels for a SaaS webapplication I am working on as a lead developer. 

The goal of the inference engine and chatbot is to be able to respond to questions posed in natural language by Slack users about problems with the SaaS application. The chatbot and the underlying engine should learn from the previous discussions and be able to correlate new questions to past issues and answer in intelligible language with a set of potential solutions.

How should I train the engine part on the Slack discussions in a way that it can utilize underlying elements to recognize and correlate new questions posed by users to past similar issues previously discussed on Slack and extrapolate a solution, formulating an answer to provide back to the user?