An AI assistant could help a prospective buyer clarify their needs, explore verified information and prepare for the next conversation.
Someone discovers the development after the sales office has closed. They want to know whether a particular layout is available and when they could visit. A form captures their details, but their questions remain unanswered. The assistant’s usefulness depends on the connection between inventory, scheduling and the people who follow through.
The visitor leaves their details in a form, but cannot find out whether the layout exists or when they could visit.
WHAT WE WOULD TESTA more useful initial conversation, with direct access to the offer and a consultant, without making public information depend on completing every sales field.
Listed as available, a proposed time and a reservation under an agreement are different states.
WHAT WE WOULD TESTConfirmation appears only after the calendar records the action. Otherwise, the inquiry is recorded with the correct status.
Context is lost between the first question and the conversation with the team.
WHAT WE WOULD TESTA complete handover that could reduce repeated preparation and help people arrive better informed.
The questions received, the distinction between an inquiry and an attended viewing, time to a meaningful conversation and why inquiries lose momentum. We would speak with the people handling them, including the questions buyers ask after seeing a floor plan.
The inventory source, how prices are presented and what each status means. If conflicting documents hold the information, resolving that inconsistency comes first.
The calendar would need to reflect actual capacity, and every inquiry would need an owner.
The question gets an answer. The viewing gets a real confirmation.
CREATIVE PROPOSAL / ILLUSTRATIVE EXAMPLEWe would use AI to interpret questions written in everyday language, explain differences supported by approved information and prepare a summary. Explicit filters, slot checks and duplicate prevention would follow controlled application rules. The interface would identify itself as an AI assistant and would not infer a person’s finances or eligibility from their name, language or other indirect clues.
The assistant asks whether the visitor would prefer to explore the layouts first or also look at viewing times.
It shows two options with terraces, with different sizes and orientations, and explains that availability for one needs to be reconfirmed by the team.
If the visitor chooses a slot, the system verifies and records it before displaying confirmation. In the demonstration, every state is simulated and labeled.
We would define the journey, fields and rules, then build the conversational interface, approved content and required connections.
We would cover a catalog outage, a slot that becomes unavailable and an absent owner. When availability cannot be verified, the response would explain that limitation and offer a route to the team.
Confirmed preferences, discussed options, open questions, appointment status and the responsible person. The team could inspect the source and correct the summary.
Every stage has an experience for the visitor and a requirement for the process.
| Stage | Visitor experience | Operational requirement |
|---|---|---|
| Discovery | Reaches the page for a relevant property type | Campaign and page preserve the offer and context |
| Clarification | Describes preferences and can correct the interpretation | Declared facts are preserved; unknowns remain visible |
| Exploration | Compares a few options and their differences | Approved information is retrieved with its verification time |
| Viewing | Chooses a time or requests a callback | The calendar confirms the action, or an inquiry is recorded with the correct status |
| Handover | A consultant continues from the existing context | Summary, source, open questions and next owner travel together |
| Follow-through | Receives the agreed information after the conversation | The team records the outcome and the appropriate next step |
Conceptual scenario. Fictional data.
A viewing accurately requested or confirmed.
Demonstration. Fictional data. Simulated actions. Scripted responses, with no connected AI, personal data, or real operations.
Records available in the fictional catalog.
Fictional data from October 8, 2026. This is not current inventory or appointment availability.
Sources and question
Choose a situation and follow what the system can verify, what stays unknown, and when a person needs to step in.
Choosing another situation restarts the demonstration.
Comparisons would account for source, opening hours, inquiry type and time to a decision. More conversations would not establish more sales on their own.
If most visitors find the answer more easily in a comparison table and a simple calendar, those features may meet the need. If inventory cannot be maintained, the assistant could focus on clarification and handover without automatically matching available units.
Review actual questions, the inventory source and what each status means.
Interface, approved content, connections and the handover view, including failure states.
Expand after quality and operation meet the agreed criteria.
An illustrative sequence; timing and investment follow the real context.