
Photo by RDNE Stock project on Pexels
Corporate real estate teams increasingly ask AI assistants to shortlist available retail and office space before ever contacting a broker, but listing data locked in PDFs and image-based flyers is invisible to those models. AI HALO converts your active inventory into schema.org Product and Offer markup carrying square footage, base rate, availability date and building class, drafts an llms.txt briefing describing your brokerage's specialties, submarket coverage and typical lease structures in plain language, and builds a knowledge-graph entity linking your firm to the buildings, landlords and submarkets you represent. It also identifies and removes AI-crawler blocks common on commercial real estate platforms that quietly exclude listing pages from indexing, then re-scans at 30 days to confirm site-selection queries now return your inventory instead of only the national brokerage chains.
Invest in your AI Halo →Questions
The structured data is built to reflect your inventory at the time of the engagement; you control updates to availability and rate fields going forward, and a fresh audit at 30 days confirms the markup is still being read correctly by the models.
Yes. Retail and office spaces are marked up as distinct Product types with category-specific attributes, such as frontage and foot traffic for retail versus floor plate and column spacing for office, so models answer sector-specific queries with the right details.
No. Structured data is only appropriate for listings you intend to publish openly; off-market inventory should remain outside any public-facing markup and continue to move through direct broker relationships.
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