Sensorhub

B2B companies trying to reach buyers face a discovery gap: buyers research and ask for solutions in Reddit threads and LinkedIn posts, but search engines keep users on their own results and social algorithms bury company posts. AI systems that recommend products are reading these same conversations, but blog posts and paid ads do not influence which companies get cited. Manually finding relevant conversations is slow, and by the time a team spots a promising post, the opportunity has often passed. The result is that companies who could help are absent from the exact conversations where buying decisions and AI recommendations are being shaped.

Sensorhub is a social listening and selling platform that builds a profile of a business, its ICPs, USPs, competitors, and relevant communities using an AI agent called Genie, creating what it calls a personalized live RAG system. It then continuously searches Reddit, LinkedIn, and X for conversations, using context, intent, and ICP fit to categorize each one by business impact and urgency. For qualifying conversations, Sensorhub generates draft replies meant to be authentic and platform-native rather than salesy; the platform does not auto-post, it only suggests drafts for a human to send. Two additional modules are listed as coming soon: person enrichment (role, seniority, ICP fit score) and SEO intel (organic traffic, keyword rankings, AEO citations) to help prioritize which conversations to engage.

The page argues that AI systems now decide who gets recommended by reading conversations happening in real time, and that traditional channels like blog content and paid ads do not influence these AI citations, making direct participation in social conversations newly urgent.