Brief capture
Budget, location, bedrooms, must-haves, timeline. AI structures the inquiry into a routable record before any human sees it.
Solution · Real estate
First reply wins the listing
OrcaLinq qualifies real estate inquiries within seconds, matches listings, schedules viewings, and pages the right agent before the visitor moves on to the next developer.
Why this fits
Speed beats sophistication in real estate inquiries
The first agent to respond wins the listing. AI-first answering qualifies the inquiry and pages the right agent in seconds — before the visitor messages three other developers.
Listing match
When a search tool is connected, AI proposes 2–3 matching listings with photos, price, and availability — fetched live, not memorized.
Viewing scheduling
Calendar integration lets the AI hold and confirm a viewing time. Without it, preferences are routed to the agent for confirmation.
Agent pickup
Right agent paged with brief and listings. They take over from WhatsApp, email, or the PWA. Customer never sees the seam.
Conversation example
From inquiry to viewing in under two minutes
A typical buy-side inquiry running through the semantic PBX. AI handles the brief; the agent owns the close.
Customer (web widget, 9:42 PM): "Hi, looking at the 3BR in Bandra West you posted. Is it still available?"
AI: "Yes, the 3BR at Hill Road is live. Asking ₹4.8 Cr, 1,640 sq ft, two parking. Are you looking for end-use or investment, and what's your timeline?"
Customer: "End-use, family of four, want to move in next 3 months. Budget up to 5.2."
AI: "Got it. I have one more 3BR you might like — 1,720 sq ft on Pali Hill, asking ₹5.1 Cr. Want me to set a viewing for either or both? Tomorrow afternoon and Saturday morning are open."
Customer: "Saturday 11 AM, both."
AI (paging agent): Brief logged, viewings reserved, agent Priya paged on WhatsApp with brief, both listings, calendar confirmation, and customer phone.
Priya (WhatsApp, 9:43 PM): "Hi Rohan, Priya from the team. Saturday 11 AM is locked for both viewings — I'll meet you at Hill Road first. Sending location pins."
Recommended setup
Three integrations and one routing policy
- Website widget on every listing page. Pre-filled with the listing slug so the AI starts in context.
- WhatsApp Cloud API number for follow-up. Most Indian buyers continue the conversation on WhatsApp; the Pod travels with them.
- Calendar tool (Google Calendar, Calendly, or your CRM's calendar) connected for viewing holds.
- Listing search tool wired to your CMS or MLS feed so AI can match live inventory.
- Routing policy with territory rules, price-band rules, and a forced-handoff list (mortgage, legal, ownership-structure, complaint).
Features used
What's doing the work
Semantic routing
Buy-side, sell-side, rental, and investor inquiries route to different agents. Out-of-territory leads escalate to the team lead.
Knowledge base AI
Building amenities, society rules, RERA numbers, floor plans, neighbourhood notes — uploaded once, cited always.
AI human handoff
Forced handoff on mortgage, refund, complaint, and high-value (>₹3 Cr) conversations regardless of confidence.
Agent-native endpoints
Agents reply from WhatsApp or Telegram on the road. No separate inbox to learn or babysit.
Audit trail
Every inquiry, every routing decision, every viewing booked — logged with timestamps, agent identity, and reasoning.
Metrics to improve
What changes after the semantic PBX is live
- First-reply time — typically drops from 20–60 minutes to under 30 seconds for AI-handled briefs.
- Inquiry-to-viewing conversion — improves when the brief is captured cleanly and the right agent is paged.
- After-hours capture — most real-estate inquiries arrive evenings and weekends; AI keeps them warm until your team is back.
- Lead-leakage to competitors — buyers message multiple agencies; the fast first reply usually wins.
- Agent time on routine briefs — falls sharply, freeing the team for closes, viewings, and negotiations.
Real estate FAQ
Frequently asked questions
Can it match listings to customer inquiries?
Yes — when a listing search tool is connected. The AI takes the customer's brief (budget, location, bedrooms) and proposes matching listings from your live inventory. Listings are fetched live, never memorized, so price and availability are always current.
What about hand-off to the agent?
Once the inquiry is qualified, the right agent is paged with the listing match, customer brief, and full transcript. The agent replies from their preferred endpoint — WhatsApp, Telegram, email, or the PWA. The Pod travels with the conversation, so handoff is seamless from the customer's side.
Can it book viewings?
Yes, with calendar integration. Without it, the AI captures preferred times, location, party size, and routes the booking request to the agent. Cancellation and rescheduling follow the same audit-logged flow.
What about regulatory disclosures?
Disclosures are policy-driven. The AI does not give legal or financial advice; mortgage, ownership-structure, and rent-control questions route to a human. Required disclosures (RERA, fair housing, etc.) can be appended to outbound messages by policy.
Can it route by territory or agent specialty?
Yes. Routing rules can match on location (city, neighbourhood, postcode), price band, property type, language, or any custom customer attribute. Out-of-territory inquiries route to the team lead instead of dropping into a void.
What if the same customer messaged us before?
Conversation memory is keyed by customer identity. Returning visitors get the same agent where possible, the prior brief is summarised for the AI, and the agent sees the full history before they reply.
Related pages
Keep exploring
See an inquiry run end-to-end.
Bring a sample inquiry email and a couple of live listings. We'll show how the brief is captured, listings are matched, viewings are held, and the agent is paged.