Our AI capabilities, described specifically.
Not buzzwords. Not features. Mechanisms. We are going to explain exactly what our AI does, because vague claims are for agencies that do not actually build things.
Conversational AI Buyer Journeys
The ad is the beginning of the conversation, not the end of it. We replace the form with a chat experience that opens the moment a buyer engages, and guides them through personalised property discovery before asking for anything.
The key principle: value before data. The AI gives the buyer something genuinely useful, curated options, EMI calculations, location insights, before it ever asks for a name or number.
The opening line
The AI's first message mirrors the ad's promise exactly. If the ad said 'Terrace homes near great schools' the AI opens: 'Looking for a home with a terrace near good schools? Want me to show you 3 options?' No drop in context.
Cognitive continuity between ad and chat is the single biggest conversion lever in the first 3 seconds.
The discovery question
One binary lifestyle or intent question. 'Terrace evenings or backyard mornings?' for family buyers. 'Steady rental income or long-term appreciation?' for investors. Not 'What is your budget?'
Binary questions are answered instantly. Open questions create friction.
Property cards
Three property cards served inside the conversation. Lifestyle photo, lifestyle caption (not a spec sheet), 2-3 features, soft inline CTA. Save, share, request details, all without leaving the chat.
Every redirect loses a percentage of buyers. Keeping exploration inside the chat preserves engagement at its peak.
The visit nudge
'Two of these homes have availability this weekend. Want me to check slots?' Not 'Book a site visit.' The AI is helping, not asking.
The visit nudge works because it follows earned trust, not cold asking.
Lead capture
Inline form: name and WhatsApp number only. Framed as slot reservation: 'I can hold a Saturday morning slot. Can I take your number to confirm?'
Capture as confirmation of a decision already made, dramatically lower abandonment than capture as application.
The handoff
Your sales team receives: persona category, lifestyle preferences in their own words, budget range, visit slot, and a conversation summary. They walk into the first call knowing the buyer.
A warm first call closes differently from a cold name in a CRM.
Creative Intelligence System
Creative fatigue is the most expensive problem in real estate marketing that nobody has a system for. Week 6, engagement drops 15%. Week 10, CPL has risen 35%. The account manager says "the market is competitive." The signal appeared in week 6.
| Signal | What it means | Decision triggered |
|---|---|---|
| CTR decay (week-over-week) | The audience has seen the creative enough times. Engagement drops before CPL reacts. | Flag the ad set. Brief replacement creative with a different visual angle for the same persona. |
| Frequency above 3.5 / week | Same audience seeing the same ad >3x weekly. Annoyance threshold approaching. | Pause the high-frequency creative. Switch from static to carousel or reel for the same persona. |
| Audience overlap above 60% | Multiple ad sets reaching the same people. Budget wasted on already-exposed audiences. | Restructure audience architecture. Exclusion lists. Lookalike expansion from converted leads. |
| Comment sentiment shift | Comments moving from curious questions to 'stop showing me this ad'. | Immediate creative pause. Emergency refresh brief. Sentiment shift is a public brand signal. |
| Post-click behaviour decay | CTR holds but time-in-conversation drops. Buyers click and leave the chat faster. | The problem is not the ad, it is the conversation entry. Rewrite the opening AI message. |
When fatigue is detected, we use AI to generate creative briefs, different visual territories, headline angles, emotional hooks. These go to human designers for execution. Speed without sacrificing craft.
AI Automation Architecture
The best sales team in Indian real estate responds in under 60 seconds. Ours does it automatically.
Instant Lead Response
Lead submits any form or completes conversational journey
Personalised WhatsApp in under 60 seconds. First name. Tone matches the persona journey. Brochure attached. Visit scheduling link.
Response speed is the single biggest predictor of whether the buyer engages with sales.
Site Visit Nurture
Visit slot confirmed
24-hour reminder with location pin, advisor name, what to bring. Morning-of reminder. Conversational tone.
Indian no-show rates are 30-40%. Simple sequences cut this significantly.
No-Show Recovery
Buyer misses confirmed slot
4 hours after: 'Life gets busy, completely understandable. Shall I check another slot this week?' Never 'you missed your appointment.'
Missed visits are leads at a different stage. Recovery treats them with respect.
Long-Cycle Nurture
Buyer in 30-180 day consideration window
Monthly construction photos. Micro-market updates. Inventory alerts matching profile. Festive content, culturally aware, not sales-heavy.
Indian property cycles are 3-18 months. Most agencies give up after 2 weeks.
Post-Visit Intelligence
Sales team logs visit outcome in CRM
Different automated sequence per outcome. 'Loved it, needs family approval' is not the same as 'comparing with another project.'
Most CRMs log the outcome and do nothing. Each exit reason is a specific new problem.
Can we predict who is going to book before the first sales call?
We are building a buyer intent scoring model based on conversational AI signals. The hypothesis: the specific way a buyer moves through a conversation, response speed, which discovery path they chose, which property cards they engaged with, whether they provided a budget range, contains predictive signals about purchase probability.
Early observation: buyers who respond to the discovery question within 20 seconds, engage with at least 2 property cards, and provide an EMI range show significantly higher visit-to-booking rates. We are formalising this into a scoring model that segments leads by intent strength before handoff to sales.
We share the hypothesis now because we think the developers who understand what is coming will have an advantage when it arrives.