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Case study: Commercial real estate

AI Leasing Agent for Commercial Real Estate

A Northeast Florida property owner needed to lease a 27,000-square-foot industrial warehouse without hiring staff to field every zoning, power, and pricing question. We gave the listing a website of its own, with an AI leasing agent that works the inquiry desk 24/7.

How the AI leasing agent handles an inquiryA prospective tenant asks a question on a dedicated marketing site for a 27,000-square-foot warehouse listing, at any hour. An AI leasing agent answers only from the property's real documents, covering the questions that arrive on repeat: square footage, clear height, dock doors, power, zoning, and the NNN rate. Every inquiry gets an accurate answer instantly, day or night. Those documents are version controlled and the owner's own team edits them directly, so a rate change updates the agent without a developer. The whole system runs on a dedicated stack built just for this client: their own automation instance, their own database, signed webhooks between components, and no credentials shared with any other system. The agent recognizes whether the visitor has a plain question, a tour request, or an LOI conversation, and captures contact details mid-conversation. A plain question is resolved in the chat without involving the team. A qualified tour or LOI lead stays on the main path to the listing broker's inbox, arriving with contact details and conversation context attached, not a bare form fill.INQUIRY DESKPROPERTY SITE“Clear height? Zoning? NNN rate?”a 27,000 sq ft warehouse listingAI leasing agentanswers only from the property’s own documentsSquare footageClear heightDock doorsPowerZoningNNN rateAROUND THE CLOCKevery inquiry, answered instantly, day or nightKNOWLEDGE BASEThe team edits it directlyspecs, rates, zoning, the FAQversion-controlled documentsNO DEVELOPER TO EDIT ITDEDICATED STACKBuilt just for this clienttheir own automation instancetheir own databasesigned webhooks, no shared credentialsOWN STACK, OWN DATABASEIntent recognizedQuestionTour requestLOIcontact details captured mid-conversationSELF-SERVEAnswered in chatresolved withoutinvolving the teamBROKER INBOXQualified lead handed offcontact details and conversation contextnot a bare form fill

The challenge

  • A large vacant warehouse generates a steady drip of repetitive questions: square footage, clear height, dock doors, power, zoning, the NNN rate
  • Every inquiry answered late is a prospective tenant who moved on to the next listing
  • The owner's team is three people, and none of them wanted to be a full-time switchboard

What we built

A dedicated single-property marketing site with an embedded AI leasing agent trained on the property's actual spec sheet, pricing rules, and leasing FAQ.

  • Answers tenant questions instantly from the real documents: specs, rates, zoning, availability
  • Recognizes whether the visitor has a question, a tour request, or an LOI conversation, and qualifies accordingly
  • Captures contact details mid-conversation and routes every qualified lead to the listing broker's inbox the moment it happens
  • The knowledge base lives in version-controlled documents the owner's team edits directly, so a rate change updates the agent without a developer

How it's built

A dedicated, isolated stack for the client: their own automation instance and their own database, with signed webhooks between components and no credentials shared with any other system. The same pipeline is being extended with a lead-pipeline dashboard and automated NNN billing through QuickBooks Online.

Results

  • Every inquiry gets an accurate answer immediately, around the clock, from the property's own documents
  • Qualified leads reach the broker with contact details and conversation context attached, not a bare form fill
  • The owner's team updates pricing and FAQs by editing a document, not by calling a developer

What does your business answer fifty times a week?

If a warehouse can handle its own inquiries, so can your front desk.