Navitec: Reactivating 30,000 Candidate Records with Echo

Turning a static ATS database into an AI-matchable talent base

The Client · Navitec is a recruiting firm running its candidate operations on TrackerRMS.

Professional Services & Staffing
01

Navitec engaged Taller to deploy Echo across its recruiting workflow and reactivate a candidate database its five recruiters had largely been unable to use.

02

Navitec held more than 30,000 candidate records inside TrackerRMS, and its five recruiters actively worked around 1,000 of them. The remainder was dormant: stale, incomplete, unenriched, and hard to search with any confidence.

The ATS held a large latent asset with no intelligence layer on top of it, so recruiters could not reliably surface past candidates for new roles, candidate data was not current enough for matching, and sourcing stayed manual. Job descriptions, resumes, and proposals were produced by hand in Navitec's own formats, adding further drag to the recruiting process.

03

Taller deployed Echo across Navitec's recruiting workflow while TrackerRMS remained the system of record, integrating the two bidirectionally so candidate, job, and application data moves between them without double entry.

The first workstream was database reactivation. Echo ingested the full TrackerRMS record set and enriched the candidate base from public professional profiles, filling in the education and work history the ATS had never captured. The second workstream was recruiting workflow intelligence, enabling AI matching, candidate assessments, ATS publishing, and custom role-status workflows mapped to Navitec's own pipeline stages, so recruiters work candidates, jobs, and applications inside Echo while TrackerRMS stays synchronized. The third was branded content generation: Echo produces custom job descriptions, tailored resumes in Navitec's multi-section CV format, and proposals exported as branded PDF and DOCX files.

Taller also customized the platform for Navitec's operating model, including a global recruiter-owner filter, AI matches scoped to the assigned recruiter, and a matched-candidate limit raised from 50 to 100.

04

Echo ingested approximately 30,762 candidate records and made them matchable. Around 24,860 candidates were enriched, and approximately 5,900 near-empty records were rebuilt into usable profiles. Ten users now work a single synced recruiting pipeline with no double entry between systems.

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