EnateAI for IDP - Document Extraction
We have added another integration to our expanding range of EnateAI components - this time we're releasing EnateAI for IDP, starting with Document Extraction. It's available now in your Enate Marketplace.
The EnateAI Document Extraction component automatically extracts the relevant data from the Files attached to incoming emails, so that this data can be used in further processing of the work item, saving your agents time and effort. Documents such as PDFs can be scanned and used both to start Cases in Enate and to form part of the ongoing process's activities.
When a Document Extraction Action runs for a Case, documents attached to the Case can be submitted to EnateAI for scanning, and processed JSON output files will be returned and automatically attached to the Case. The JSON files give you a structured breakout of data from within these documents, allowing for much easier and slicker downstream processing by further external systems and technologies.
If at any point EnateAI is not confident enough of the results, based on a confidence threshold that you can set, Enate will instantly transfer the work to an agent in Work Manager to look over and verify, giving you that 'human in the loop' support.
How does EnateAI Document Extraction work at runtime?
When a case is started in Enate by an incoming email with files attached, the agent can assign Tags to the individual files (or you can use EnateAI's Document Classification integration to have the system do this for you automatically). Once this is done, the case can move onto an EnateAI Document Data Extraction Action which has been set in the case flow.
The action will process all files that are tagged with the tags it has been configured to pick up. Once processed, if EnateAI is confident in its extraction results, the action will continue to the next point in the case flow, without the agent needing to intervene. A JSON output file of the extracted data (in a structured format) gets attached to the case, and the action will close automatically. Agents can still click to view the Action if they wish to, which will show the completed document extraction(s) and any output JSON files in the 'Files' tab.
Agents can verify when AI isn't confident enough - 'Validation Station' screen
If EnateAI confidence in its data extraction result drops below the designated threshold, the system will automatically set the action to be picked up by a human agent to process. When the agent opens the action they will see that it is in a state of 'To Do' - any documents needing their input will be marked with 'Requires verification'.
To verify the problem files the agent just needs to click on the 'Verify Now' button and scroll to the EnateAI Validation Station screen to review and amend contents.
On this validation screen the agent will be able to see a scanned copy of the file, which can be multiple pages, alongside three tabs showing extracted data.
The Extracted Data tab shows the agent key value pairs of the extracted data along with the confidence level that EnateAI has given them. The values can be adjusted when necessary and are saved once the agent clicks the update button for that value. Doing so will set the confidence value to 100% for that Key.
The Tables tab shows any repeating data that has been picked out as a table.
The Additional Data tab shows additional data that has been picked up from the document. EnateAI's document data extraction technology allows Agents to take this kind of data and actually promote it up to being a Key / Value pair that will be shown on the Extracted Data tab, allowing the Agent to not just adjust the proposed values of recognized keys but also adding further keys if they have not been picked up.
If the agent needs to leave the Validation Station screen at any time they can just click 'Save as Draft' to save their changes. Once an agent is happy with the data all they need to do to submit the updated data is to click 'Submit Validation'.
Once all files requiring verification have been verified by the agent, the action will automatically be marked as Resolved and will then move to Closed.
Configuring EnateAI for IDP - Document Extraction
Setting up EnateAI for IDP - Document Extraction is extremely quick and simple - only two quick steps are needed:
Switch on EnateAI - Document Extraction in Builder's Marketplace
Add an 'IDP Data Extraction Action' into your Case flow.
How to Activate EnateAI for Document Extraction in Marketplace
To activate the EnateAI Document Extraction component, Builder users navigate to the Enate Marketplace, use the filters (Provider and/or Category) to find the component and then click to activate. This will instantly activate the component without the need to input any additional keys as would be needed with similar integrations provided by external technologies .
How to configure EnateAI for Document Extraction Actions into your Cases
You can then add 'IDP Data Extraction' Actions into your desired Case flows in Builder. You can either add an existing one from the Actions list if one has already been created, or you can create a brand new one. To create an IDP Document Extraction Action in a Case, from the Action selection drop-down select to create a new Action.
Give the Action a name, add a description if you wish and for its type, select 'IDP Data Extraction Action'. When you click 'OK, the Action will be created and added to the Case flow.
On the Action Info tab you will need to set when it's due and set an Allocation rule (i.e. where to route the Action if it needs to be manually reviewed by an Agent when the technology's confidence levels aren't high enough).
There's also general settings for the Action too, and ability to set a custom card, again only really for use in the unlikely event that someone needs to intervene and view the action in Work Manager - though remember that the Validation Station screen will automatically show in such circumstances.
Next, go to the 'IDP Document Extraction tab' for the Action to define the settings which specifically relate to the approval activities.
You'll need to fill in:
The Extraction Model - this is the ID of the model you want to use for that process. See this section for more information on Extraction Models.
The Input File Tag - the tag that the document must be tagged with in order for the Action to pick it up and perform data extraction on it. For example, setting this to 'Invoice' will ensure that only files tagged as 'Invoice' will be picked up. All other documents will be ignored by the Action.
The Output File Tag - the tag that the Action will assign to the file once the document extraction process has completed. For example, you may want to set a value of 'Processed' for any documents will have been picked up.
Once you have filled in the above settings details, you can set the Case live and you'll now have automatic document data extraction working on your Case process.
Extraction Models Available
EnateAI offers a range of extraction models to use when configuring your IDP Document Extraction action.
The current Extraction Models available are:
Business Card
Contract
General Document
Health Insurance Card
ID Document
Invoice
Receipt
US Tax Document Model
All of these Extraction Models come from Azure's official list of pre-trained models ensuring an industry standard. More of Azure's pre-trained models will be made available for users of EnateAI in coming releases. If you wish to investigate these extraction models further, follow the link below to Azure's official documentation:
Other Providers
In addition to EnateAI, other Integration Providers can be found within Marketplace which provide this kind of Document Data Extraction, including Infrrd and AzureAI. More integration providers will become available in Marketplace over time.
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