S.B.M Recruiters Cuts Hiring Cycle by 48%

S.B.M Recruiters is a US based staffing and talent solutions firm specializing in Health Information Management (HIM) roles such as medical coders, clinical data analysts, health record auditors, and compliance officers. With healthcare compliance standards tightening and demand for HIM professionals rising, the firm needed to handle large candidate pipelines while ensuring accuracy, speed, and regulatory adherence.

To improve hiring efficiency and compliance, S.B.M Recruiters implemented our Resume Management System (RMS) an AI driven recruitment platform designed through advanced machine learning practices to centralize candidate data, job matching, client management, and interview scheduling. By consolidating fragmented recruitment workflows into one system, the agency reduced manual errors, shortened hiring timelines, and enabled data informed decision making that enhanced both candidate and client satisfaction.

• Sector: Human Resource, Recruitment
• Project Type: Centralized Candidate and Hiring Workflow Solution
• Platform: ReactJS | .NET 8 | SQL | Blob Storage | Azure CD | Document Intelligence

• Fragmented Resume Handling – Candidate resumes were scattered across emails, spreadsheets, and third-party platforms, leading to delays in retrieval and duplicated records.
• Compliance Risks – Healthcare recruitment required strict adherence to HIPAA, credentialing, and audit standards. Manual verification and documentation increased the likelihood of compliance lapses.
• Slow Candidate Shortlisting – Recruiters manually scanned resumes for job matches, slowing down the shortlisting process and reducing responsiveness to clients.
• Weak Client & Candidate Visibility – Clients lacked real time status updates, while candidates had no visibility into progress, creating frustration on both sides.
• Scheduling Inefficiencies – Coordinating interviews between multiple stakeholders often resulted in scheduling conflicts and missed opportunities.
• Limited Data for Strategic Decisions – Without analytics, the firm couldn’t measure hiring trends, placement success rates, or recruiter performance effectively.

• Centralized Candidate Database – All resumes, profiles, and supporting documents were unified into one secure repository with deduplication and advanced indexing.
• AI Driven Job Matching – Intelligent algorithms analysed resumes against job requirements to produce ranked candidate lists, reducing manual screening effort.
• Compliance Integrated Workflows – Built in credential verification, document expiration alerts, and HIPAA compliant audit logs ensured regulatory adherence across every hire.
• Client & Candidate Portals – Provided real time dashboards where clients could track shortlisted candidates and candidates could view application status, creating transparency.
• Automated Interview Scheduling – Coordinated calendars across candidates, recruiters, and clients, auto suggesting available slots and reducing back and forth emails.
• Data Analytics & Reporting – Delivered insights on time to hire, placement success, and recruiter performance, supporting continuous improvement and data informed strategies.

This end to end recruitment system was developed using a secure, cloud native approach aligned with Azure. Our team configured Blob Storage, automated deployment pipelines, and document intelligence APIs to optimize scalability, data protection, and performance.

By combining AI innovation with strong enterprise grade software engineering, the solution enabled S.B.M Recruiters to transform complex hiring workflows into an intelligent, compliant, and transparent digital ecosystem.

• Hiring cycle reduced by 48% – Average time to fill positions dropped from 42 days to 22 days, improving client satisfaction and win rates.
• Placement accuracy improved by 37% – AI job matching reduced mismatched placements, ensuring higher retention rates for candidates placed in HIM roles.
• Compliance error rate reduced by 82% – Automated credential checks and audit ready logs minimized compliance risks and eliminated costly rework.
• Scheduling conflicts reduced by 70% – Automated interview coordination cut delays, ensuring faster progression from shortlisting to final selection.
• Recruiter productivity increased by 33% – With AI screening and streamlined workflows, each recruiter handled more active roles without compromising quality.
• Enhanced client trust – Real time dashboards gave clients full visibility into progress, improving transparency and long-term relationships.
• Operational savings of 1,800 staff hours annually – Automation of resume screening, compliance verification, and scheduling freed up recruiter capacity for strategic engagement.