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FAQ
Straight, sourced answers to the questions Indian real estate developers and presales teams actually ask about AI voice agents, one use case per page.
Site-visit conversion improves at three points: a faster first call catches the buyer while intent is still high, structured qualification filters out leads that were never going to visit so the team stops wasting slots, and the agent books the visit directly on the call instead of leaving it as a follow-up task. On a typical manual process, roughly 2-6% of raw portal leads become a site visit; developers running fast AI-driven follow-up push that to 8-12%.
AI wins on speed, consistency, and coverage: it calls every lead within 60 seconds, at any hour, asks the same qualification questions every time, and never skips a retry. Humans still win on negotiation, judgment calls, and relationship-building once a lead is qualified. The practical shift isn't replacing the presales team, it's changing where their time goes.
Call within minutes, not hours. Every additional minute of delay reduces the odds a lead answers, engages, or eventually books a site visit, because in most Indian markets the same buyer is browsing 2-3 competing projects on 99acres, MagicBricks, or Housing.com at the same time. Thinkly AI's voice agents place the first call within 60 seconds of a lead landing in your CRM, in the language the lead used to submit the enquiry.
Thinkly integrates with your CRM, not with property portals directly. Leads from 99acres, MagicBricks, Housing.com, JustDial, and CP networks already flow into your CRM the way they do today; the voice agent picks them up the moment they land there and writes qualification data, call recordings, and next steps back automatically.
Thinkly AI agents cover 30+ Indian languages and dialects, including Hindi, Hinglish, Marathi, and English, with natural mid-sentence code-switching, which is how most real qualification calls in India actually sound rather than an edge case.
Yes, but only because it's built around real estate-specific qualification logic and project data, not adapted from a generic customer-service bot. Each project gets its own knowledge base covering configuration, possession timeline, payment plans, and common objections, and questions outside that scope are escalated to a human rather than guessed at.
The agent retries automatically at different times rather than dropping the lead after one attempt. A missed call at 9pm doesn't mean the lead wasn't interested, it usually means they were driving, in a meeting, or didn't recognise the number, and consistent retry recovers a meaningful share of leads a manual process would let go cold.
Most "AI for real estate" pitches fall into four categories: chatbots or WhatsApp bots, traditional IVR, voice AI agents, and call analytics/QA. Chatbots and IVR sit on the margins of the actual bottleneck, which is phone-based; only voice AI agents and call analytics directly touch the manual calling and coaching gap on a presales floor.
Efficiency gains come from removing manual work, not adding a dashboard. Automatic transcription and scoring of every call removes the hours a manager spends listening to a small sample, and objection and drop-off mapping across the full call volume shows exactly where a team's time and site-visit slots are being spent on calls that were never going to convert.
Coaching improves when it's based on the full call volume instead of a small manual sample. Thinkly's call analytics scores every conversation against a custom rubric, builds a performance heatmap per rep, and surfaces exactly what your top performers do differently, so 1:1s are specific and evidence-based rather than based on a manager's memory of a handful of calls.
See exactly how Thinkly fits your sales operation in 30 minutes.