Case Study

AI Streamlines Candidate Sourcing & Decision-Making

Key Challenges

During a two-day Artificial Intelligence & Machine Learning Workshop (AI&ML), in which we explore practical applications of AI for businesses, we worked with a technology staffing firm to identify inefficiencies in their candidate selection process. Recruiters were manually matching key skills from job descriptions to a large pool of resumes. Once potential candidates were identified, their existing software lacked effective filtering and parsing capabilities, hindering targeted searches and making it difficult to prioritize candidates in terms of suitability for the role.


Our Solutions 

BridgeView worked closely with the client’s leadership to understand their current business processes and isolate pain points. We then identified opportunities to meet those challenges with AI&ML Solutions included:

AI-powered Skill Extraction: An intelligent layer was built on top of their existing software, using AI to automatically extract key skills from job descriptions.

Advanced Search & Ranking: Recruiters can now run targeted searches based on extracted skills and then prioritize the most qualified candidates.

Seamless Integration: The solution seamlessly integrates with their current software’s functionality, allowing recruiters to continue to operate within the existing program while acting on top candidates more efficiently.


Impacts & Outcomes

The company is currently rolling out the solution, with initial results showing significant promise:

Reduced Search Time: Recruiters can identify top talent faster, freeing up valuable time for interviewing and vetting candidates.

• Improved Candidate Identification: Dynamic skill matching ensures recruiters focus on the most qualified individuals, enhancing the overall quality of hires.

• Streamlined Workflow: The intuitive interface simplifies the candidate selection process, boosting recruiter productivity.

Thinking Beyond Technology: By directly addressing real-world business challenges through AI&ML – not just technical limitations – we freed up the client’s team to do what they do best.


Technologies or Methodologies Used:

• Robotic Process Automation (RPA)

• Large Language models (LLM)

• Applicant tracking system (ATS)

• Node-Red

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