Hudson Talent Solutions Partners with Maki People to Embed AI Hiring Intelligence Across Its Global RPO Delivery

The partnership marks one of the first integrations of a dedicated AI hiring intelligence system into a top-tier RPO offering

Hudson Talent Solutions, one of the world’s leading recruitment process outsourcing providers, and Maki People, the AI hiring intelligence company, announced a strategic partnership that will bring faster, more accurate hiring decisions to Hudson Talent Solutions’ clients worldwide. By embedding Maki People’s AI hiring intelligence platform directly into its delivery model, Hudson Talent Solutions will give clients access to structured candidate insight at every stage of the funnel, from the first application through to final selection.

For hiring teams, this means shorter time-to-hire, higher-quality shortlists, and a more consistent candidate experience at scale. Every decision made through the system feeds back into it, building a richer picture of what drives hiring performance than any static process ever could.

Under the agreement, Hudson Talent Solutions will integrate Maki People’s platform across its hiring programs, enabling its clients to leverage AI-driven hiring intelligence from the earliest stages of the funnel through to final selection.

Catch more HRTech Insights: HRTech Interview with Bernard Barbour, Chief Technology and Product Officer at Skillsoft

Redefining what RPO delivers

The partnership reflects a broader shift in how RPO providers are expected to compete: not just on operational excellence and global reach, but on the quality and speed of hiring decisions at every stage of the funnel.

Maki People’s system deploys specialized AI agents across the candidate journey, feeding structured hiring intelligence back to the teams that need it. For Hudson Talent Solutions’ clients, this translates into faster time-to-hire, higher signal-to-noise in candidate selection, and a more consistent candidate experience at scale. Critically, every decision made through the system feeds back into it, building a richer picture of what drives hiring performance than any static process ever could.