AI for candidate sourcing and recruitment
Client: One of the largest candidate search and recruitment companies in the US
Objective: To come up with AI that sources active and passive candidates and hiring authorities, continuously updating contact information with features like batch email, smart matching and geomapping.
To use NLP and OCR (computer vision) to parse thousands of customer emails, online reviews, detect mood vectors and provide early warnings and advice to a company on any changes and their drivers then channel using chabots the right email to the right person at the company who is best suited to address concerns. Data was also used to perform analytics at a higher level to leverage the company’s capabilities and customer service.
Solution: Company data collected over the years from multiple sources along with captured real time data from company websites and public social media platform were used to create a continuously updated database. Predictive modeling that learns from recruiters within a user-friendly dashboard allows for candidate sourcing and filtering; enabling easy matching and inventory control.
System promises to dive into all the incoming text/images the client receives through various channels – emails, chats, HR tickets, support forms so as to, classify it and trigger specific processes set-up for a particular subject or point the data flow to the correct agent.
- Deliverable: A smarter AI-powered recruitment system
- Technology: Syntax, Semantics, Discourse, Data mining,cleaning and structuring. Deep learning and multicrawler system.
- Outcome: Automated recruitment system and personalized recruiter experience that improved company performance.