linkedout

You can search your LinkedIn connections using natural language by asking plain English questions to find contacts by company, role, location, or skills. The Skill interprets your query and returns matching professional profiles from your network.

Yes, you can find contacts at specific companies or in certain locations by asking structured queries. The Skill filters your professional network data based on company, role, location, and skill parameters to identify relevant connections.

Semantic search for professional network analysis uses embeddings to find connections based on meaning rather than exact keywords. This allows you to discover profiles with similar roles or skills even if the search terms do not match exactly.

Yes, you need a local database to enrich LinkedIn profile data. The Skill supports integration with local databases using psycopg2 to store and query enriched profile information, career histories, and funding data for intelligent recommendations.

The best way to identify contacts at startups for investment discussions is to ask semantic or structured queries about your network. You can find connections at specific startup stages and locations, then access career histories and warm introduction pathways.

Limitations when querying LinkedIn network data include dependency on your existing connections and the quality of enriched data in your local database. Semantic similarity searches require embeddings and may not return results for highly niche or unrepresented professional roles.