Five asset classes. One intelligence layer.
The underlying platform is constant. What changes by asset class is which signals matter and how far ahead of the market they can be detected.
Unit-level demand, tracked before renewal season.
Ownership concentration, refinancing activity, and renewal patterns are mapped at the unit level across every property in a submarket, so acquisition and value-add opportunities surface before they reach a broker's pipeline.
Tenant flight risk, surfaced before the lease expires.
Sublease listings, headcount signals, and space utilization patterns are combined to flag tenants at risk of departure months ahead of the lease event, giving landlords and brokers time to act.
Foot traffic and co-tenancy, mapped corridor by corridor.
Traffic patterns, anchor tenant stability, and co-tenancy fit are scored at the corridor level, identifying which vacancies are winnable and which repositioning moves actually lift sales for neighboring tenants.
Listing and pricing signals, days ahead of the MLS.
Owner tenure, permit activity, and pricing behavior across a draw area are combined into a ranked list of the households most likely to transact, before they appear as an active listing.
Absorption and lease rollover, mapped by submarket.
Occupancy, lease expiration, and logistics demand data are tracked across every submarket, surfacing rollover risk and absorption opportunity well before renewal conversations begin.
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