IntentLeads.ai

The idea came from repeatedly seeing the same pattern across different projects: people openly ask for recommendations, tools, and services every day on public platforms, yet most businesses never see those conversations in time. While teams spend significant resources on ads, cold outreach, and broad targeting, genuine demand is already being expressed in plain sight. The inspiration was simple—if users are already saying what they need, there should be a better way to notice and respond to that intent.The core problem was inefficiency in customer acquisition. Traditional methods focus on pushing messages outward rather than listening for signals of demand. This creates wasted effort, low response rates, and long sales cycles. I wanted to solve the gap between when a user expresses a need and when a business becomes aware of it. Most tools either measure engagement or brand mentions, but very few focus on identifying decision-ready intent. The goal was to help teams spend time talking to people who actually want a solution, instead of persuading people who don’t.Initially, the idea was closer to a general social listening tool. Over time, it became clear that volume and visibility were less important than relevance and timing. The process evolved toward filtering aggressively and prioritizing clarity of intent over scale. We refined how intent signals are defined, focusing on language patterns like requests, comparisons, and explicit problem statements. The launch process itself followed the same principle: test quickly, listen to real usage, and remove anything that didn’t directly support finding meaningful demand. The result is a simpler product that does fewer things, but does them with much higher signal quality.