Reactivating a Dormant Candidate Database with AI Recruiting Workflows

A staffing and recruiting firm engaged Taller to reactivate its dormant candidate database and deploy Echo across its sourcing and recruiting workflows.

The client had more than 30,000 candidate records inside its applicant-tracking system (ATS, the platform recruiters use to store and manage candidates), but only around 1,000 were actively worked by its five recruiters. The rest of the database was stale, incomplete, unenriched, and hard to search with confidence. Recruiters could not reliably surface old candidates for new roles, the candidate data was not current enough for matching, and sourcing stayed manual. Job descriptions, resumes, and proposals were produced by hand in the firm’s formats, adding more drag to the process. The ATS was a storage system without an intelligence layer, and without one, the firm’s largest candidate asset stayed effectively invisible.

Echo was deployed across the client’s operation while its ATS remained the system of record. Taller integrated the two systems bidirectionally so that candidate, job, and application data could move between both platforms without double entry.

The first workstream was database reactivation and enrichment. Echo ingested the client’s full ATS record set, enriched candidates through LinkedIn, and rebuilt profiles that had held no usable data. This turned the candidate base into an AI-matchable talent pool.

The second workstream was recruiting-workflow intelligence. Echo enabled AI matching, candidate assessments, ATS publishing, and custom role-status workflows mapped to its pipeline stages, so recruiters could work candidates, jobs, and applications inside Echo while both systems stayed synchronized.

The third workstream was branded content generation. Echo produced custom job descriptions, tailored resumes in the firm’s multi-section CV format, and proposals exported as branded PDF and Word files. Taller also configured Echo to the firm’s operating model, including a global recruiter-owner filter, AI matches restricted by assigned recruiter, and a matched-candidate limit raised from 50 to 100.