Case Study

MatchCraft Talent Matching SaaS

An AI-assisted talent matching product concept with PRD-driven execution and agent-friendly docs for fast iteration.

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Problem

Talent sourcing is noisy and manual; matching candidates to roles often depends on inconsistent reviewer judgment and scattered notes.

Constraints

  • Needs explainable matching (not just scores)
  • Should fit a lean MVP scope for quick validation
  • Must support a clean workflow for clients and internal reviewers

Solution

Defined a structured pipeline (intake → normalize → match → shortlist → feedback loop) with a clear PRD/agent workflow so implementation can be delegated to coding agents effectively.

Impact

  • Reduced time-to-shortlist with structured intake and ranking
  • Improved consistency via repeatable evaluation criteria
  • Created a scalable base for iterative matching improvements