Tenant data
A retail tenant database that answers your space
Most tenant databases hand you a list and wish you luck. Atlas starts from the unit you are trying to fill, searches thousands of retail operators and brands against it, and comes back with the ones that actually fit, each with the person who signs the lease.
Credits per search, not per seat. Atlas is $200 a month, and a single signed lease pays for years of it.
The problem with buying a list
A static retail tenant directory is a snapshot of who exists. That is not the question a landlord or broker has. The question is which of them would take this unit, at this size, on this street, this year. A list cannot answer that, so the work of turning twelve thousand rows into a shortlist of forty lands back on you, and it is the part that takes the weeks.
Atlas inverts it. You describe the space once, or drop the brochure and let it read itself, and every search runs against that specific unit. What comes back is not the database. It is the shortlist, with the reasoning attached.
Four ways Atlas looks for a tenant
Every search runs all four at once, because the right tenant for a unit arrives by different routes depending on the block.
Operators outgrowing their unit
Businesses trading nearby whose current space is visibly too small for what they are doing: the queue out the door, the storage in the corridor. They are the likeliest movers on any block.
The category your block is missing
What the surrounding streets already sell, and what they do not. A block with three coffee shops and no bakery tells you what the next tenant should be.
Brands with announced expansion
Chains and regional operators that have publicly said they are opening in your market, matched against the format your unit can actually house.
The best-rated operators around
The independents a neighbourhood already rates highly, which are the ones a landlord most wants and most rarely hears from.
What a record actually contains
A tenant directory entry that stops at a company name is where most tools give up. Every match Atlas returns carries the things you need before you would pick up the phone:
- Why this business, for this unit, the specific signal that surfaced it, written out rather than scored.
- The size it usually takes, against the size you have, so a mismatch is obvious before the conversation.
- How many locations it runs and whether it is currently expanding.
- Its footprint and rating in the surrounding market, what the neighbourhood already thinks of it.
- The decision-maker, with a verified email: the owner, franchisee or head of real estate, not a reception address.
From the shortlist to a signed lease
A database is the first third of the job. Atlas is built for the whole arc, and is honest about which parts have shipped:
Described once, understood properly
Drop a brochure PDF and the form fills itself. Atlas reads the address, the unit, and the streets around it: what trades nearby, what the block is missing, what footfall it carries.
Matched, ranked, and explained
Not a list of every business in the county. The ones that fit this unit, each with the reason it was picked, the size it usually takes, and whether it is expanding.
The decision-maker, with a verified way in
A tenant match is useless without a name. Atlas finds who actually signs at each business, whether that is the owner, the franchisee or the head of real estate, and verifies the email before it hands it over, and the credits come back when nobody reachable exists.
Outreach drafted for you
Coming shortly: the AI assistant writes the first message for each tenant, in your voice, citing the specific reason that business fits this specific unit, which is the thing that actually gets a reply, and tracks the thread to a signed LOI.
Who this is for
Landlords with a vacancy who do not have a leasing team and are tired of waiting for a marketplace listing to work. Brokers running a book of listings who need a defensible candidate list per space, fast, and something specific to say in the first email. If you want the method rather than the software, the guide to finding commercial tenants lays out the same approach by hand, and the comparison of tenant search tools is an honest read on where a marketplace or a data platform beats this.
What it costs
Atlas is $200 a month with 10,000 credits, spent in any mix of searches, contacts and AI outreach drafts; the credit costs page lists what each uses. A contact that turns out to be unreachable refunds itself. Full detail on the pricing page.
Stop buying lists. Search your actual unit.
Describe the space once. Atlas reads the address, the streets around it and the businesses in them, and comes back with matched tenants and the person to contact at each.
Run your first search