Alex Dudov
⬤ LangChain just dropped PeopleHub, an AI system that makes LinkedIn research ridiculously simple. Instead of manually digging through profiles, you can just ask questions in plain English and get structured insights instantly. Built by Meir Kadosh with help from the LangChain community, PeopleHub runs on the LangGraph framework to handle everything from profile parsing to activity tracking and automated reporting.
⬤ Here's how it works: the platform pulls LinkedIn profile data, user activity, and relevant signals through a central LangGraph agent that manages the entire process. It transforms raw data into clean profile summaries, activity breakdowns, and polished reports. The smart caching system eliminates repetitive tasks, which is how they're cutting research costs by 70–90%. That's a massive efficiency boost for anyone working at scale.
⬤ PeopleHub is perfect for analysts, recruiters, compliance teams, and business development folks who live on LinkedIn. You type in what you need, and the system generates detailed profile reports, pulls together historical activity, and helps you make better decisions faster. The open-source release on GitHub includes workflow examples showing exactly how LangGraph routes queries, extracts data, and produces outputs.
⬤ This launch shows just how much demand there is for AI research tools in enterprise settings. Companies need massive amounts of professional data to guide hiring, partnerships, and investments, and PeopleHub proves AI agents can replace manual grunt work and speed up due diligence. LangChain's focus on transparent, modular automation is shaping the future of enterprise intelligence.
Alex Dudov
