mudpie

Company profile · 3 min read

Tandem: AI-native office leasing with local brokerage support

Tandem combines market-wide office search, tours, negotiation and local brokerage support for teams leasing in San Francisco, New York and Boston.

Published · Updated

Tandem is an office broker built around the whole market, not one broker’s memory.

What it does

The current Tandem homepage says tenants can search offices across landlord listings, broker inventory and off-market opportunities, then move from shortlist to tours with local support. Its current markets are San Francisco, New York and Boston. The company says tenants use Tandem for free because the brokerage is paid by the landlord when a lease is signed.

That model matters. Office search is not only a discovery problem. The buyer needs to know what is actually available, what it costs, who controls the space and whether the deal fits a short-term or shared-office need. Tandem’s public story is strongest where the AI improves market coverage and the human team handles tours and negotiation.

Why I’d look closer

The YC profile says Tandem was built for smaller units, shorter terms and shared/common areas that traditional brokerage can underserve. The homepage says it offers next-day tours, market insight and expert negotiation. It also displays customer quotes from companies including Headout, Norm AI and Numeric; those are company-selected testimonials, not an independent review base.

Rafi Sands’ public background is relevant: the YC profile says he spent two years at Stanford researching the post-COVID office market under Professor Nick Bloom. Brendan Suh is listed as cofounder and COO. That helps explain the company’s market-data angle, but the final lease decision still needs a human broker and legal review.

What I’d ask

I would ask how inventory freshness is checked, how off-market listings are verified, how tenant representation is disclosed, and what the California agency disclosure says. The checked packet includes a mandatory California disclosure document, which is a reminder that “free for tenants” does not mean the brokerage relationship is irrelevant.

My editorial take

Shortlist Tandem if you are leasing in one of its covered markets and care about speed, comparison and negotiation more than a single familiar broker relationship. It is less useful outside those markets or when you already have a landlord-side deal in motion.

Quick facts

Field Sourced detail
Product AI-native office leasing brokerage
Buyer Startups and teams searching office space in SF, NYC or Boston
Pricing Free to tenants; company says landlord pays on signed lease
Human layer Local team handles tours, negotiation and lease path
Main question How fresh and complete is the inventory for your exact market and term?

Sources checked

Source Checked
YC company profile 2026-09-19
Tandem homepage 2026-09-19
Tandem about 2026-09-19
California agency disclosure 2026-09-19

Cohort context

Tandem is listed in Summer 2024. In our 2026-09-18 directory snapshot, 161 of 248 listed companies in that cohort have YC’s primary industry label B2B (64.9%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.

Public website snapshot

Observed 2026-09-19T16:17:44.237Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

Signal Homepage observation
Product description metadata Observed
Canonical link Observed
H1 or H2 heading Observed
Typed structured data Observed
Docs/developer link Not observed in this response
Pricing link Not observed in this response
llms.txt link Not observed in this response
Markdown alternate Not observed in this response

Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.

About the author

I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.

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