Sourceress offers a sourcing product that takes a call with hiring managers to infer the attributes they truly want and then builds models to surface candidates who fit that intent even if they lack explicit qualifications. The company scours public signals — GitHub, papers, Stack Overflow and similar sources — and post-processes features to identify transferable skills and latent fit. Today Sourceress focuses on engineering and product roles, tuning its algorithms with each hire so the models become more abstract and eventually automate profile inference. The team says its approach helps surface more diverse candidates and reports that 30–40% of its hires are women and minorities. There is currently no candidate-facing product, but the company envisions a future hub or matching layer similar to Indeed, Hired, or LinkedIn for passive candidates. Sourceress raised new financing to support product development and model tuning.

Total raised

$4M

Funding rounds

1

Latest round

Equity

Latest activity

Nov 2017