ML-Powered Matching Engine for an HR Technology Platform

The Challenge

An HR technology platform had no dedicated data department to manage fragmented data across their CRM, POS, and accounting systems. This fragmentation hindered cross-relational analytics and made scalable Machine Learning matching impossible. There was no single view of resource planning, making it difficult to match job seekers with opportunities effectively. The platform was growing rapidly but their data infrastructure couldn't support the complexity of their matching algorithms or provide the insights needed to optimize their marketplace.

Our Solution

Polar Packet built centralized infrastructure for cross-relational insights, unifying data from all systems into a single platform. For a major acquisition (BetterPlace), we developed ML-based supply-demand matching algorithms for job posts and job applications. Our team created the data foundation that enabled sophisticated matching capabilities, turning fragmented data into a competitive advantage.

The Results

• Decreased operational turnaround time by 40%
• Achieved 3x faster profile matching for business opportunities
• Continued 2-year retainer from day 1 through acquisition
• Clear data strategy and outsourcing capabilities to tackle complex data infrastructure
• ML-based matching algorithms powering the core product experience
• Unified data platform enabling cross-system analytics and reporting
• Scalable infrastructure supporting rapid business growth
• Successful data integration during BetterPlace acquisition