Lantern AI
Lantern is an agentic recruiting platform that combines a World People Model of over 1 billion indexed profiles with a Company Hiring Model that learns a team's hiring taste from past decisions. Its AI agents handle sourcing, application review, interviews, and analytics, sharing context so each search improves the next. The platform reports 84% faster time-to-fill and has processed over 2 million candidates.
- HR Technology
- AI Agents
- Artificial Intelligence
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Traditional hiring software is a system of record—it stores what happened but does not know the market and does not learn. Each new hire starts from scratch because sourcing, interviews, and decisions each keep their own notes, leaving no accumulated understanding across roles.
Solution
Lantern is an agentic recruiting platform that combines a World People Model with a Company Hiring Model to give recruiting agents shared context across sourcing, application review, interviews, and analytics. The World People Model understands career context—who built what, at what company stage, and what titles actually meant there—informed by over 1 billion indexed profiles. The Company Hiring Model learns a team's taste from open reqs, HM kickoff notes, debrief calls, ATS history, and past decisions, so each agent works from the same hiring bar. Sourcing agents explore beyond keyword matches by considering open-source contributions, forums, Discord, YouTube, and other public clues. What one agent learns is available to the next, while your team stays in control with human sign-off on final decisions.
Target Audience
Primary customers are hiring teams and recruiting organizations at technology companies, particularly those hiring for engineering, product, and founding roles where traditional keyword sourcing misses strong candidates.
Features
- World People Model with over 1 billion indexed profiles and company data for understanding career paths, company context, and actual work built
- Company Hiring Model that learns taste from HM kickoff notes, debrief calls, ATS history, and past decisions, connecting learning across every open req
- Natural-language sourcing that finds talent beyond boolean keyword filters, exploring domain specialists, adjacent industries, and emerging builders in parallel
- Multi-channel candidate intelligence following public contributions across open source, forums, Discord, YouTube, Instagram, and X
- Three starting points for a search: role description, intake recording of the brief conversation, or similar profiles that set the hiring bar
- MCP client and MCP server integrations to connect company context and expose Lantern's sourcing capabilities to a team's own tools and agents
- Outreach drafting to email, LinkedIn, and iMessage that opens with a candidate's actual work and why the role fits