Crawler
Connected Python pipelines crawl open-web registries and third-party databases, surfacing verified candidates in a dedicated recruiter web app with map search, relationship graphs and self-serve pipeline runs.
ITSUA designs, builds, and operates custom web applications for product teams in 20+ verticals. Consider starting own project similar to this one.
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Sourcing licensed specialists across a distributed network is slow and patchy.
Hiring managers had to comb through public registries by hand, and once a name surfaced there was no clean way to verify work history or find a warm-intro path.
Connected Python pipelines. Two ways in.
| L1 · Crawl | A graph of connected Python scripts against public licensing registries | Python + MySQL | Authoritative baseline |
| L2 · Enrich | Joins against professional networks and third-party contact databases, scored into a graph of coworker and location ties | Python + MySQL | Work history + warm-intro paths |
| L3 · Surface | A recruiter web app: office search on a map, specialist profiles with a relations graph, XLSX/PDF exports, user management with 2FA, activity log by business unit | Vue · Nest | One source of truth |
| L4 · Operate | Pipelines run from the app one at a time, with dry runs, snapshots and a change report on every run | Nest · Python | No engineer in the loop |
A live, fully-automated sourcing pipeline.
Weeks of manual trawling replaced with fresh monthly leads — each candidate arrives with verified credentials, a reconstructed work history, and a warm-intro path. Recruiters search offices on a map, trace a specialist's connections in a relations graph and export shortlists; admins manage users and 2FA, follow activity by business unit, and rerun the pipelines themselves, with a dry-run report before anything reaches production.