6 Best AI Lead Generation Tools for Real Estate (2026)

Ylopo combines AI-powered Facebook and Google advertising with an AI chatbot (rAIya) that qualifies leads before they reach you. The chatbot handles initial conversations via text, asking qualifying questions and gauging timeline and motivation. By the time a lead hits your CRM, you know their budget, timeline, and level of seriousness. The AI ad optimization continuously improves targeting based on which leads convert.

Cinc (Commissions Inc.) has refined its AI lead nurturing over years of real estate-specific data. Its AI assistant Alex handles long-term lead nurture via text and email, re-engaging cold leads that would otherwise die in your database. The platform's strength is working leads over months, not days—Alex follows up with behavioral triggers until the lead is ready to engage with an agent.

Zurple tracks lead behavior on your IDX website and uses AI to send personalized follow-up based on the specific properties they viewed. If a lead looks at three homes in Brentwood above $600K, Zurple's AI sends targeted communication about that search pattern. The behavioral intelligence is genuinely useful for personalizing outreach at scale.

Structurely is a pure AI lead qualification service—it doesn't generate leads but qualifies ones you already have. Its AI assistant Aisa Holmes handles text and email conversations with new leads, asking qualifying questions and booking appointments with your calendar. For agents drowning in leads they can't respond to fast enough, Structurely solves the speed-to-lead problem.

Real Geeks combines an IDX website, CRM, and AI chatbot in one platform. The AI chatbot engages website visitors, the property alert system keeps leads engaged, and the Facebook ad integration drives traffic. It's less sophisticated than Ylopo or Cinc but significantly more affordable, making it a practical choice for agents starting with AI lead generation.

Offrs uses predictive analytics to identify homeowners likely to list in the next 12 months based on public data, behavioral signals, and AI modeling. The concept is powerful—prospecting before leads self-identify—but results are inconsistent. Hit rates vary significantly by market, and the predicted sellers still require significant prospecting effort to convert.