01 Brooklyn Heights
2-bedroom condo
Within stated budget
Real estate · Property discovery and listing search
Help people find the right property without starting from a filter panel
Property search usually begins with a sentence. Traditional property search asks the user to translate those needs into filters. A conversational search can do that translation. The AI Agent can understand the request, ask a few useful follow-up questions, search the available property data, and surface listings that better match what the person is looking for.
People start with requests like
“I need a two-bedroom near downtown under $3,000.”
“We want a house with a yard and good access to the train.”
“I’m looking for a condo with a doorman and gym.”
“I need something available next month.”
Property finderIllustrative search
Buyer request
I’m looking for a two-bedroom condo in Brooklyn under $1.2 million.
Example resultsSeveral listings match
ListMap
01
02 Cobble Hill
2-bedroom condo
Within stated budget
03 Boerum Hill
2-bedroom condo
Within stated budget
Example listing cards. Property details depend on the connected listing data.
Show relevant listings, not just a list of links
The AI Agent can surface property results in a structured format that makes comparison easier. A listing result might include a property image, address or neighborhood, price, bedrooms and bathrooms, square footage, property type, key amenities, availability, a short property summary, and the next action. This allows the user to compare several options without leaving the conversation immediately.
The translation behind the search
People search in sentences.
Listing databases search in fields.
Real estate databases are structured. People are not. The AI Agent can bridge that gap. Instead of making the user decide every filter before seeing a result, the conversation can progressively refine the search.
What the person says
“I want something quiet, close to the subway, with two bedrooms and enough space to work from home.”
Intent becomes criteria
01Property type
02Location
03Price range
04Bedroom count
05Square footage
06Transit proximity
07Building amenities
08Outdoor space
09Move-in date
010Availability
Turn broad intent into usable search criteria
The AI Agent can help narrow requests across the criteria that matter to the business and the listing data available.
LocationNeighborhood, city, school area, commute preference, proximity to transit, or other location criteria supported by the data.
BudgetPurchase price, monthly rent, or a preferred range.
Property typeApartment, condo, co-op, townhouse, single-family home, multifamily property, or other categories.
SizeBedrooms, bathrooms, square footage, or room requirements.
FeaturesOutdoor space, elevator, parking, doorman, gym, laundry, pet policy, home office, or other listing attributes.
TimingMove-in date, availability, lease timing, or purchase timeline.
The conversation can collect only the details that materially improve the search.
Search is a conversation, not a one-time query
Start broad, then narrow naturally
A property search does not need to begin with ten questions. The AI Agent can start with the request the person already has.
Example conversationBrooklyn property search
BuyerThe interaction feels like a property search, not a form.
The first result set is often not the final one
01Show me something cheaper.
02Only keep listings with outdoor space.
03Can you move the search closer to the train?
04I don’t want a high-rise.
05Show me similar properties in another neighborhood.
06Only show units available next month.
The person stays in the same conversation while the search becomes more precise.
Property discovery
Property discovery can work for buyers and renters
The same conversational model can support different property-search journeys. The data and instructions determine what each search experience can support.
Buyer search
Purchase price, property type, neighborhood, bedrooms, building type, ownership structure, and relevant listing attributes.
Rental search
Monthly rent, move-in date, lease availability, pet policy, amenities, and location.
Relocation search
Help someone unfamiliar with the area narrow neighborhoods based on the criteria the business has chosen to support.
Investment-property search
Where appropriate, help users filter available listings by property type, location, price, and other factual investment criteria without giving individualized financial advice.
Connected listing data
Search across structured listing data
This use case becomes especially powerful when AskHandle can search current property data rather than rely on static website copy. Structured listing information may include the fields below. The AI Agent can use that data to return more relevant results based on the user’s request.
Listing dataConnected source
AListing IDBStatusCAddressDNeighborhoodEPriceFProperty typeABedroomsBBathroomsCSquare footageDAmenitiesEAvailabilityFAgentAOpen-house informationBListing URLCProperty images
Keep property details grounded in the listing source
Real estate information changes.
Prices move. Availability changes. Listings go under contract. New properties appear. The AI Agent should use the connected listing data as the source for property-specific answers.
If a listing is no longer available or the requested information is missing, the conversation can say so and help the person continue the search. This keeps the experience useful without inventing property details.
Example
Refine instead of restarting
The conversation keeps the context and progressively narrows the search.
Example renter searchIllustrative results
Different real estate businesses focus on different markets.
Make the property search feel like your business
An AI Agent can reflect that. That allows a brokerage, property manager, rental agency, or real estate team to create a search experience around the properties they actually represent.
01Service areas02Listing types03Neighborhoods04Property categories05Price ranges06Supported search criteria07Agent assignments08Listing data sources09Availability rules010Escalation instructions
Built with AskHandle
Build a conversational property search
This use case can be created using AskHandle nodes and AI Answer skills.
AI Answer
Understand natural-language property requests, answer general property questions, and guide the search.
Data Search
Search structured listing data based on criteria such as location, price, bedrooms, amenities, or availability.
AI Answer with Product Cards enabled
Present property results as structured visual cards with relevant listing details.
AI Answer with Image Answers enabled
Surface property images or visual listing information in the conversation.
Question Flow
Ask a small number of structured follow-up questions before useful results can be returned.
Human Handoff
Help when the person wants to speak with an agent, has a complex request, or needs support beyond the available listing data.
Property discovery and listing search
Make property search more conversational
People already know how to describe the home they want. They should not have to learn the structure of a property database before they can search it.
A conversational listing experience lets them start naturally, refine as they go, and compare relevant properties without repeatedly rebuilding the search. The data stays structured. The experience feels human.
Explore AI agents for real estateCan the AI Agent search live property listings?
Yes, when current listing data is available through the connected data source used by the workflow.
Can users search by neighborhood, price, bedrooms, and amenities?
Yes. The AI Agent can search and refine based on the structured fields available in the listing data.
Can it show several properties at once?
Yes. With AI Answer with Product Cards enabled, property results can be presented as structured cards for easier comparison.
Can users change their search without starting again?
Yes. The conversation can retain the existing criteria and adjust individual preferences as the user refines the search.
Can the AI Agent recommend which property someone should buy?
It can help users discover and compare listings based on the criteria they provide. Final property decisions and professional advice remain with the user and relevant real estate professionals.
Can the conversation move from discovery to a viewing request?
Yes. Once the user finds a property they are interested in, the workflow can continue toward a viewing request or Human Handoff.