Case Studies/Qualigence
RecruitingOps Efficiency

An AI Sourcing Agent That Cut Sourcing Time 36.2%

36.2%

Sourcing Time Saved

100%

Fit-Scored Before Any Enrichment Spend

Self-improving

Sourcing Rounds

Revenue Institute built Qualigence an AI Sourcing Agent: give it a job description and it finds the candidates, scores their fit before a dollar of data spend, enriches the ones worth pursuing, and learns from every recruiter judgment. Result: 36.2% of sourcing time returned to the recruiters.

Context & Challenge

Qualigence is a recruiting and talent firm. Sourcing is the grind under every search: writing search strings, combing profiles, judging fit one by one, and paying for data enrichment on candidates who were never right to begin with. It is skilled work - and it is also the first hours of a recruiter's day, every day.

Recruiting margins live and die on sourcing hours. Every search starts the same way: a recruiter translates the role into search strings, pages through profiles, judges fit one by one, and pays for contact data on their best guesses - including the guesses that turn out wrong. Off-the-shelf AI sourcing tools promise to fix this and mostly relocate the problem: they return long lists of weak matches, so the recruiter still does the judging, now with worse raw material. Qualigence needed the judgment automated, not just the searching.

Our Solution

The Full First Pass, Automated

Revenue Institute built a sourcing agent that runs the full first pass of a search. From a job description, it constructs the search queries a senior sourcer would write, sweeps the public web for matching profiles, and - before any paid enrichment - grades every candidate for fit on a 1-to-10 scale against the role.

Spend Only on Scored Fits

Only candidates who clear the bar get enriched with verified contact data, so the data budget follows the AI's judgment instead of funding its mistakes.

Recruiters Train It With a Thumb

Recruiters stay in command with a simple thumbs up or thumbs down on the agent's picks; the system converts that feedback into sharper include-and-exclude filters for the next round, so it learns the firm's taste for every role.

Blocked From Making Things Up

Because the agent drafts candidate-facing material downstream, it is mechanically blocked from fabricating: any claim it cannot trace to a real source becomes a bracketed gap for a human to fill, never an invention.

The Results

36.2% of Sourcing Time, Returned

Measured across the firm's searches, the sourcing agent cut sourcing time by 36.2%. The hours moved to where they matter - the conversations with candidates - and the capacity gain came without adding a sourcer to payroll.

Data Spend Follows Judgment

Enrichment is purchased only after the AI has scored a candidate as a fit. The spend that used to subsidize wrong guesses now follows a graded shortlist.

It Gets Sharper Every Round

Recruiter feedback is not a satisfaction survey - it is training signal. Every thumbs up or down rewrites the next round's filters, so the agent converges on what a great candidate looks like for each client and role.

Trust, Enforced by the System

Everything the agent writes traces to a real source - enforced by gates the software will not open, not by policy. For a firm whose product is its credibility with candidates, that guarantee is the feature.

"If you're an operations leader who wants to see what AI actually looks like in practice - not in a demo, but in your business - this is the team."

Janelle Osborne, COO, Qualigence

Key Results Achieved

  • 36.2% Sourcing Time Saved

  • Data Spend Follows Judgment

  • Sharper Every Round

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