We delivered an AI Recruiting Strategist for a Mid-Size Staffing Agency

A staffing agency placing forty to sixty candidates a month across light industrial, administrative, and skilled trades now has an AI Recruiting Strategist that treats their existing database like a goldmine instead of a graveyard. The system semantically scores every inbound resume against all open requisitions simultaneously — not keyword matching, but understanding that "managed a crew of twelve on commercial HVAC installs" maps to a superintendent role even though no keyword overlaps. It resurfaces dormant candidates from the agency's own ATS who placed elsewhere two years ago and might be ready to move again, ranking them by predicted receptivity based on tenure patterns and market signals. For active outreach, it drafts personalized messages calibrated to each candidate's likely motivators — a foreman gets stability language, a project engineer gets growth language — and A/B tests subject lines across segments. It monitors pipeline velocity per requisition and alerts recruiters the moment a role's candidate flow drops below the rate needed to fill by deadline, recommending whether to widen geography, adjust compensation positioning, or shift sourcing channels. The agency owner went from gut-feel pipeline management and missed fill deadlines to a data-driven recruiting floor where no req goes stale without someone knowing exactly why.