Product · MVP build
Building TalentCache AI from idea to working platform.
Project summary
TalentCache is proof of a different claim: that we can build an AI product outright, not just automate around one. We took a recruitment idea from nothing to a working platform, live at talentcache.ai.
The problem
Recruiters sit on thousands of CVs they cannot search by meaning. Finding a candidate means keyword guesswork and folder archaeology, while inbound CVs pile into inboxes untouched. The product had to make a CV base genuinely searchable, and keep itself fed.
What we built
- A CV pipeline that parses real-world documents at scale, then scores candidates and extracts their skills with AI.
- AI-matched candidate search for agencies, with a credits model built into the platform.
- Mailbox integration live end to end, so inbound CVs flow straight into the system without a human touch.
The result
The idea became a working product in production. CVs arrive by mailbox and flow into the system without a human touch, get parsed and scored at scale, and become searchable by meaning rather than keyword. Built and shipped end to end by the same architects who sit on our roster.
Before
A recruitment idea with no product behind it, and CV bases that could only be searched by keyword.
After
A live platform at talentcache.ai parsing CVs at scale, scoring candidates and matching them by meaning rather than keyword.
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