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Solutions · Commercial real estate

AI agents for commercial brokerages, landlords and property managers

We build an inquiry agent that answers portal and website leads from your own listing sheets, asks what the tenant needs and books the tour on the broker's calendar, so a lead that arrives at night has an answer before morning. We also rebuild your listing and market pages so ChatGPT, Perplexity and Google's AI answers can quote them when a tenant asks for office space for lease in Markham.

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The problem

Where time and leads slip away today

  • 01

    Portal leads wait until morning

    An inquiry from LoopNet or Spacelist lands late in the evening, asking for the additional rent and whether the unit has a drive-in door. The broker is at a showing the next morning and replies after lunch. By then the tenant has booked tours elsewhere.

  • 02

    Every inquiry asks the same things

    Size, net rent, additional rent, parking, zoning, possession date. It is all on the listing sheet, and someone still types it out again for each inquiry on each portal.

  • 03

    Tenant requests arrive everywhere

    A rooftop unit stops cooling and the tenant reports it by email, then by text to the property manager's cell, then to the superintendent in the hallway. Later, nobody can say when it was first reported or who closed it.

  • 04

    Listings that AI assistants cannot read

    When a tenant asks an AI assistant for office space for lease in Markham, the answer is built from pages that state size, rent and availability in plain text. A listing that is a photo carousel and a PDF brochure gives it nothing to quote.

The solution

What we build for you

  • Listing inquiry agent

    Reads lead emails from each portal and your website form in the inbox they already arrive in. It answers from the listing sheet, asks about size, use, move-in date and when the current lease ends, offers tour times from the listing broker's calendar and writes the exchange to your CRM. Questions the sheet does not answer go to the broker.

    Custom AI agents

  • Tenant request intake

    One address for maintenance requests. The agent asks for the unit, a description and a photo, opens the work order in your property management system and tells the tenant when its status changes. Sending a vendor or approving a cost stays with the property manager.

    Custom AI agents

  • Lease and document questions

    Staff ask questions of your leases and building documents and get the answer with the clause it came from: which tenants have a renewal option coming up, or who pays for HVAC repairs at a given property. We train the team to read the clause before acting on it.

    Custom AI agentsAI training for teams

  • Listing and market pages that get cited

    Each listing becomes a page with its facts in text and structured data, and your market reports become submarket pages that answer tenants' questions directly. We fix the technical SEO, add an llms.txt file and track which AI answers mention you.

    AEO, GEO & SEOWeb development

  • Follow-up after the tour

    Tenants who toured and went quiet hear from you when the asking rent changes or a comparable unit comes up. The broker approves each message before it goes out. Every touch is logged in the CRM, so you can see which listings produce leads.

    Marketing automation agents

Case study

How it runs in practice

Cases marked “Example scenario” show how a typical project runs. We are replacing them with named client results.

Commercial real estate

Example scenario

An inquiry agent that answers listing questions within minutes

A commercial brokerage in the GTA

First reply to a portal inquiry
< 5 min
First reply to a portal inquiry
Tours booked from portal leads
1.5×
Tours booked from portal leads

The brokerage lists office and industrial units on several portals, and every inquiry lands in one shared inbox. Brokers reply between showings, often the next day, and most first replies repeat what is already on the listing sheet.

  • Read portal lead emails and website form submissions from the shared inbox the team already uses.
  • Answer only from each active listing sheet: size, net rent, additional rent, zoning and possession date.
  • Ask about size, use and move-in date, then offer tour times from the listing broker's calendar.
  • Log every conversation and tour in the CRM, and pass rent negotiation and anything not on the sheet to the broker.
Custom AI agents

First 90 days

FAQ

Commercial real estate: common questions

Does it work with the portals we already list on?

Yes. Most portals send each inquiry as an email, so the agent reads them from the inbox they already arrive in and nothing changes on the portal side. Where your CRM or a portal offers an API, we connect to that as well.

What if the agent quotes the wrong rent?

It answers only from the listing sheets you give it, and it says so when a detail is missing instead of guessing. When a sheet changes, you update it once and the agent uses the new figure from then on. Every reply is logged, so you can see what was said and when.

Will it negotiate terms with a tenant?

No. It can share the asking rent and anything else on the published sheet. Offers, free rent, improvement allowances and anything that commits the landlord go to the broker with the conversation attached.

Can a broker take over a conversation?

Yes. Every conversation sits in your inbox or CRM, and a broker can reply at any point. Once they do, the agent stops answering on that thread.

Can you get our listings cited by ChatGPT or Google's AI answers?

We can make them easy to find and quote: facts in plain text, structured data, fast pages, an llms.txt file and submarket pages that answer the questions tenants ask. Nobody can promise a citation, so we track which answers mention you and rework the pages that are not being picked up.

Next industryFinancial services

Tell us about the workflow that costs you the most time

A first call is about the business you run, not a pitch. We will tell you what an agent could handle, what it should not, and what it would take to build.

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