*We are using a fictional name and logo for this case study at the request of the client.
Seisan worked directly with key stakeholders to create a functional requirements document that defined scoring logic, job-specific criteria, integration requirements, and performance expectations powered by scalable cloud compute and local AI intelligence.
Develop a system that can reliably ingest, extract, score, and rank applicants and generate a consistent, detailed report.
Seisan delivered a customizable automated resume gathering and extraction engine that ingests large volumes of applicant data, analyzes each resume against job- specific criteria, and generates a ranked candidate report.
A leading mechanical supplier specializing in plumbing and HVAC distribution, sought a way to efficiently manage a growing volume of job applicants across multiple locations. Their HR team routinely received hundreds of resumes per day, each requiring consistent evaluation, scoring, and ranking. Seisan developed a fully automated, backend-driven resume screening system capable of processing high-volume applicant data while aligning with strict business rules, on-premises data requirements, and the company’s existing HR ecosystem.
The Company’s HR department was overwhelmed by the sheer number of applicants flowing in daily. Traditional manual review processes created delays, inconsistencies, and bottlenecks—especially when roles required highly specific technical experience.
Key challenges included:
APR needed a system that could reliably ingest, extract, score, and rank applicants—with zero UI requirements—while generating a consistent, detailed report for hiring managers every morning.
During development, Seisan identified performance limitations in the initial LLM provider. The team pivoted to a higher-performing model that ensured overnight processing could be completed reliably without impacting scoring accuracy.
Additionally, inconsistencies between UKG’s public documentation and actual API behavior required iterative testing and custom handling to ensure seamless integration.
Core capabilities included:
The backend service was deployed in AWS EC2 while maintaining full compliance with APR’s requirement for on-premises AI processing.
To ensure reliability and accuracy, Seisan executed:
Once validated, the system was deployed and integrated into APR’s nightly hiring workflow.
The Company’s HR team now benefits from a dramatically streamlined applicant screening process:
The system eliminated manual screening bottlenecks and provided APR with a reliable, technology-driven hiring advantage— improving efficiency while preserving full control over applicant scoring criteria.
