On November 24, 2025, the Department of Justice filed a proposed settlement with RealPage Inc., the Texas-based software company whose revenue management tools recommended rent prices for more than 24 million units worldwide. The terms require RealPage to stop using nonpublic, competitively sensitive data from competing landlords when generating rent recommendations. A court-appointed monitor will oversee compliance for three years.
The settlement arrived after a fourteen-month federal prosecution. In August 2024, the DOJ sued RealPage under Sections 1 and 2 of the Sherman Act, alleging the company pooled confidential lease data from rival landlords and fed it into pricing algorithms that pushed rents upward across entire markets. By January 2025, the department had expanded its case, filing an amended complaint naming six of the country's largest rental operators: Greystar, LivCor, Camden, Cushman & Wakefield, Willow Bridge, and Cortland. Together, these companies manage more than 1.3 million units in 43 states.
The core allegation was structural, not incidental. Landlords who competed for the same tenants were sharing real-time lease data through a common software vendor, and the software was converting that shared intelligence into pricing guidance. According to the DOJ, this functioned as a price-fixing mechanism with an algorithmic middleman.
Greystar, the largest private landlord in the United States, settled separately. A federal judge in North Carolina approved its consent decree on March 2, 2026. Greystar also paid $50 million in a private class-action and $7 million to resolve claims brought by a coalition of nine state attorneys general led by California's Rob Bonta. Cortland entered a consent decree requiring it to stop using competitors' data and to cooperate with federal investigators.
RealPage did not admit wrongdoing. Under the proposed settlement, its algorithms must be retrained to exclude active lease data from unaffiliated properties, relying only on backward-looking data at least 12 months old. Geographic modeling below the state level is prohibited, and features that discouraged landlords from cutting prices must be removed.
The case did not emerge in isolation. Before her departure from the DOJ in February 2026, Assistant Attorney General Gail Slater said she expected algorithmic pricing investigations to increase as adoption of the technology spread. Slater added that sharing information through an algorithm provider could create the same anticompetitive effects as a direct exchange between competitors. The agreement with RealPage runs seven years, subject to extension.
State legislatures moved in parallel. California's Assembly Bill 325, signed by Governor Newsom in October 2025 and effective January 1, 2026, amended the Cartwright Act to prohibit the use or distribution of common pricing algorithms for collusion. The law applies to any algorithm with two or more users that incorporates competitor data, and a companion bill raised antitrust penalties to $6 million per corporate violation.
New York amended the Donnelly Act effective December 15, 2025, targeting algorithmic rent-setting specifically. Connecticut passed its own version with a narrow carveout for publicly available data. California's law, unlike New York's, is not limited to residential real estate. In 2025 alone, 24 state legislatures introduced more than 50 bills to regulate algorithmic pricing.
The legal framework is still forming. In Gibson v. Cendyn Group, a Ninth Circuit panel ruled unanimously that competing Las Vegas hotels did not violate antitrust law merely by licensing pricing software from the same vendor. The distinction that mattered was whether the software pooled private competitor data or simply used publicly available market information.
The RealPage case fell on the other side of that line.
What began as a dispute over rent prices has become a broader test of whether antitrust law can keep pace with algorithmic coordination. The software at issue did not require landlords to speak to one another; it replaced the conversation with a data pipeline and an optimization function.
Whether that constitutes an agreement under the Sherman Act is a question federal courts are still answering.
