Generative AI + Specialized AI Community Challenge + Job Posting Request Intake

[Jon_Smith]

Generative AI + Specialized AI Community Challenge + Job Posting Request Intake

Use Case Description

This use case describes a business process at a recruitment company. This recruitment company receives job postings from their clients that they need to add to their recruitment application. The job postings can be submitted by their customers in multiple different ways to maximise their intakes and they have multiple customer portals:

• They are sent via email to the recruitment company
• They need to be retrieved from Customer Portals using UI interaction
• They need to be retrieved from Customer Portals using APIs
  To retrieve all the necessary information of the job posting, information can be retrieved from the email body, the Customer Portal, and, most importantly, from the Job Posting Document.
  The first step to retrieving all the necessary information is extracting information from the Email or Customer portal that is not in the Job Posting Document. This information is then sent to Data Service, along with Job Posting Document.
  The Job Posting Document is then converted to a pdf file and picked up by a Document Understanding process. This Document Understanding process uses a custom build ML Skill that has been trained in AI Center. If the information cannot be extracted with a high enough confidence, a extraction validation task is created for the business in Action Center.
  When all the information has been extracted from the Job Posting Document, specific business rules need to be applied to the data. Examples of this are:
• The enddate cannot be before the startdate.
• Hours per week needs to be between 4 and 40.
  These rules are hosted in a Django database. The business can maintain these rules through a UiPath app that is build as a layer over the Django database.
  Furthermore, some fields need very specific formatting before being entered into the Recruitment Company’s application. To apply this formatting the text is sent to a LLM that is hosted on Azure with very specific instructions, like:
• Add HTML headers to the text
• Create HTML list items if applicable
  All of the formatted and transformed data is then sent to a final unattended process that enters all the data in the Recruitment Company’s application.
  This process greatly improves the company’s time to market and saves their recruiters valuable time, that they can now use to find the right people for the jobs!

AS-IS WORKFLOW, TO-BE WORKFLOW

Other information about the use case

Industry categories for this use case: HR

Skill level required: Advanced

UiPath Products that were used: UiPath Studio, UiPath Action Center, UiPath AI Center, UiPath Apps, UiPath Data Services, UiPath Document Understanding, UiPath Orchestrator

Other applications that were used: Azure Open AI, Django

Other resources: This is a real use case that we have implemented with a customer at Ciphix so can advice from real experience.

What is the top ROI driver for this use case?: Accelerate growth and operational efficiency

[Ka_Ho_So]

Great work Jon and good luck with the contest!

[loredana_ifrim]

Hi @John_Smith thank you for submitting your use case. Don’t forget to share it on your social media followers to cast their vote for your use case! Votes will be counted till November 10, 2023 Stay connected .