@TechTalk LUIS offers pre-built domains for your apps that are authored with the resource. These domains are not specific to certain area or an industry but these are a set of common entities and intents that get added to your app so you need not create them manually. For example, If you add the calendar pre built domain it adds examples related to some common phrases like
Please create a meeting from 2 to 3 and tags 2 as the calendar.starttime and 3 as calendar.endtime. This is really helpful if your end user types in something like this as it automatically tags these entities and provides you an output in response which can be used for further processing. This allows you to build phrases specific to your business logic and train the models further.
You can import data from a CSV file to LUIS but the format of the file or columns need to setup based on the programmatic API request parameters. An example of this scenario is listed in our documentation with a sample app.
Yes, if you want to build a bot with a FAQ or Question & Answer scenario then LUIS & QnA can be integrated with your bot framework. For all these scenarios you can use QnAMaker along with sharepoint. But the document format is important to check if QnAMaker can parse these documents to create a knowledge base. Ideally, QnAMaker is useful if you have a long FAQ type document with question and answer format or a sheet with data mapping between columns.
If you would like to lookup questions like
Show me all contracts with notice period 'less that 60 days' with 'expiry in 2020'? Then, QnAMaker would not be able to pull this data as this time/date dependent lookup. This can be achieved if you integrate your bot with a DB source to run a query where you can use LUIS to extract information like Year:2020, Validity: <60, Type:expiry and run this query against your backend DB source. In this case, LUIS app needs to be trained with the appropriate entities and intents by adding such phrases in the training phase. The biggest advantage of these scenarios is you can train your model incrementally instead of covering all scenarios from day 1. This helps you review the questions customers are asking and modify your app to include all phrases that might have been missed.
Yes, data can be fetched from a file which is in the required format from SharePoint if you are using QnAMaker and it can be added as KB.
Form recognizer can be used for any valid file formats. The standard models available will help you recognize standard formats like receipts but if you have clauses in paragraphs you can still use the Form recognizer labeling tool to train and label certain sections. Using a labeling tool is very simple to use and you can try this out by downloading the container to check if this works for your doc format.
Cognitive services can be integrated with PowerBI and one of the common scenario is sentiment analysis and key phrase extraction. PowerBI documentation provides an example or tutorial that can help you get started.