50 qualified leads per week — sourced, enriched, and contacted automatically.
This agent uses linkedin_scraper (4k+ GitHub stars) to enrich every prospect with real LinkedIn data: name, headline, work experience, education, skills, and company details (industry, size, founding date, specialties). It builds ICP-targeted lead lists, writes personalized outreach referencing each prospect's actual profile, and manages 3-touch follow-up sequences. Built-in dashboard tracks your pipeline from sourced → contacted → replied → meeting booked.
Free to start — no credit card required
A Python library built on Playwright for extracting structured data from LinkedIn profiles, companies, and job listings. Uses async architecture with Pydantic models for type-safe data, reusable authenticated sessions, and progress tracking callbacks.
Specify industry, company size, role, and tech stack. The agent builds targeted lead lists matching your criteria and pulls each prospect's LinkedIn profile data — headline, experience, education, skills, and company info.
linkedin_scraper extracts structured profile data: work experience with dates, education background, skills inventory, and company details (industry, size, specialties). Outreach emails reference something specific — a recent role change, shared alma mater, or company milestone.
Automated 3-touch cadence over 10 days with personalized follow-ups. Replies flagged instantly. Dashboard tracks pipeline funnel: leads sourced → contacted → replied → meeting booked, plus open rate and reply rate.