AI Systems Instructor • Real Estate Technologist
Quick Answer: RealScout is an AI-powered property matching platform that goes beyond basic MLS search to understand buyer behavior and lifestyle preferences. Best for buyer's agents who want intelligent property recommendations and collaborative search boards. Rated 7.5/10 for real estate. Starting at $39/agent/month.
Goes beyond beds/baths/price to match buyers with properties based on behavioral signals, lifestyle preferences, and implicit criteria the buyer may not have articulated. Learns and improves with every interaction.
Shared boards where agents and buyers save, rate, and discuss properties together. Every thumbs-up or thumbs-down trains the AI to better understand what the buyer actually wants, creating a feedback loop that gets smarter over time.
AI-curated property alerts that adapt to buyer behavior rather than rigid criteria. If a buyer consistently clicks on homes with large yards despite not listing it as a requirement, the AI adjusts alerts to prioritize outdoor space.
When you list a property, RealScout's AI identifies matched buyers across its agent network and sends targeted alerts. Your listing reaches buyers whose behavior patterns suggest they'd be interested—not just those searching the right zip code.
AI-generated market insights for specific property types and neighborhoods. See which buyer profiles are most active, what price ranges are getting the most attention, and which listing features drive the most engagement in your market.
Connects with Follow Up Boss, kvCORE, and other major CRMs to sync buyer activity data. Agent sees which properties a lead is viewing, saving, and sharing—providing context for every follow-up conversation.
AI Acceleration teaches RealScout as the 'buyer intelligence layer' in your tech stack. While your CRM manages the relationship, RealScout's AI manages the property search intelligence—surfacing the right homes and giving you data-driven talking points for every buyer conversation.
Use the 5 Essentials to build a comprehensive buyer profile. Task: find their ideal home. Audience: this specific buyer. Materials: their stated preferences, lifestyle priorities, dealbreakers, and nice-to-haves. The more detailed the initial profile, the faster the AI learns.
Set up shared boards with your buyers. Show them how to rate properties (thumbs up/down, notes). Every interaction trains the AI. Encourage them to interact with listings even when you're not available—the AI captures everything.
Before every buyer call, check their RealScout activity. Use their viewing patterns as Materials in a HOME Framework prompt to draft personalized property recommendations: 'Based on the 12 properties Maria saved this week, all had modern kitchens and large backyards. Here are 3 new listings that match that pattern.'
After showings, run the OODA Loop. Observe: did the buyer like the AI-recommended properties? Orient: if not, what did the AI miss? Decide: update preferences or add new criteria. Act: refine the profile and watch the AI adapt.
Prompt
[RealScout AI Matching — Buyer Behavior Analysis] Buyer: David and Sarah Chen Stated criteria: 3-4BR, $500-650K, Franklin TN RealScout behavioral data (past 3 weeks): - Saved 14 properties, skipped 47 - 12 of 14 saved have open floor plans - 11 of 14 saved have 0.25+ acre lots - Average saved home price: $612K (trending higher than initial range) - Consistently skip: homes on busy roads, homes with pools - 3 saves in Cool Springs area specifically Using this data as Materials in a HOME Framework prompt:
Output
**HOME Framework Prompt (for Claude or ChatGPT):** Hero: You are a buyer's agent in Franklin, TN with deep knowledge of Williamson County neighborhoods. Outcome: Draft a property recommendation email to David and Sarah Chen highlighting 3 new listings that match their actual preferences (not just stated criteria). Materials: - They say they want 3-4BR, $500-650K, Franklin - Behavioral data shows they actually prefer: open floor plans (85% of saves), larger lots 0.25+ acres (78% of saves), Cool Springs area specifically, no pools, not on busy roads - Their actual comfortable price point appears to be ~$610-650K based on save patterns - They haven't stated the open floor plan or lot size preferences explicitly Execute: Warm, knowledgeable tone. Reference specific neighborhood details. Under 200 words. Do not mention that you're tracking their browsing behavior—frame recommendations as your market expertise. **AI Output:** Subject: Three Franklin homes I think you'll love David and Sarah, Three new listings hit the market this week that immediately made me think of you: 1. **4247 Cool Springs Blvd** — 4BR/2.5BA, $625K. Open-concept main floor with a kitchen that flows into a great room with vaulted ceilings. Sits on a third of an acre on a quiet cul-de-sac in Cool Springs. No pool, low-maintenance landscaping. 2. **1188 Briarwood Lane** — 3BR/3BA, $639K. One of the more spacious floor plans in this price range—the main level is almost entirely open. Half-acre lot backing to a greenbelt. Cool Springs schools. 3. **892 Fieldstone Dr** — 4BR/2BA, $618K. Recently updated with a modern open layout. Quarter-acre corner lot on a dead-end street. Five minutes to Cool Springs Galleria. Any of these worth seeing this weekend? I can set up tours Thursday or Friday. Best, Amanda
RealScout's AI did the heavy lifting here—identifying that the Chens' behavior reveals preferences they never stated: open floor plans, larger lots, and Cool Springs specifically. The agent used this behavioral intelligence as Materials in a HOME Framework prompt to create a recommendation that feels like expert local knowledge rather than algorithmic tracking. This is the Context Over Cleverness principle in action: the right data (behavioral signals) fed into the right structure (HOME Framework) produces output that feels human and thoughtful.
Other tools real estate agents use for similar tasks.
All-in-one platform with smart IDX and CRM—broader feature set but less specialized in property matching
Full platform with IDX search and CRM—more features but less sophisticated property matching AI
Best CRM for lead management—pairs well with RealScout for buyer intelligence
Learn the Frameworks