GLOSSARY

Semantic Sourcing

Semantic sourcing uses AI to understand natural language queries (e.g., "DevOps AWS 5 years Paris available March") and retrieve relevant candidates without Boolean search.

IN DEPTH

Semantic sourcing is a candidate search method based on AI natural language understanding, without Boolean operators. The user formulates the query as if speaking to a human ("DevOps AWS engineer 5 years experience available March in Paris with remote"), and the AI returns the most relevant profiles from internal pool + external sources. Semantic sourcing understands industry synonyms, context, seniority levels, and even indirect signals (recent LinkedIn position change = openness signal). It advantageously replaces Boolean search which becomes ineffective beyond 10,000 profiles. Measured impact: -70% search time, +300% relevant profiles identified, -30 to -40% candidate acquisition cost. Cobalt offers native semantic search integrated in the ATS.

Frequently asked questions

On average -70% search time (30 min to 9 min for complex query) and +300% relevant profiles. Beyond 10,000 profiles in database, the gain is even more massive as Boolean becomes unusable.

Cobalt (EU leader, native natural language semantic search from Starter plan €31). Loxo (US, good on AI sourcing). Legacy ATS (Bullhorn, Vincere) still rely on Boolean search. Productivity gap becoming massive.

Related terms

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