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AI-Powered Candidate Research & Scoring Pipeline
Turning an afternoon of manual candidate research into a Slack notification.
Challenge
The client, a talent agency, was spending hours manually researching and scoring candidates before they could be shortlisted for a role. This slowed down the evaluation process and made it hard to apply consistent criteria across every candidate reviewed.
Resolution
- Built an N8N automation that pulls public information on each candidate via Serper
- Passed the research results to Claude, which scores each candidate against a defined set of criteria
- Automatically generated a full evaluation report in Notion, including strengths, concerns, and an overall fit score
- Notified the evaluator via Slack as soon as each report was ready
Impact
- Replaced a manual research process that previously took the team an entire afternoon per batch of candidates
- Delivered a structured, ready-to-review evaluation report the moment the pipeline finishes running
- Cut the feedback loop from hours down to minutes by notifying evaluators instantly via Slack
Stack
Tools used: N8N, Claude, Serper, Notion, Slack
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