Reservoir Media sues Suno for $157.5 million over AI training data

The core of the lawsuit

Reservoir Media Management, a prominent independent music publisher, has filed a lawsuit against the AI music generator Suno. The company is seeking $157.5 million in statutory damages for the alleged unauthorized use of 1,050 musical compositions. These works include famous tracks like Joni Mitchell's "Big Yellow Taxi" and Johnny Cash's "Ring of Fire."

The complaint argues that Suno used these copyrighted works to train its models without paying any licensing fees. Reservoir Media claims that because Suno's training data includes essentially all music files accessible on the open internet, its own catalog was necessarily included. The publisher wants up to $150,000 for each of the 1,050 songs identified in the filing.

Beyond the primary copyright count, the lawsuit includes claims for breaking through website protections. Reservoir also alleges that Suno stripped out songwriter credits during the data collection process. The company is demanding a jury trial to resolve these disputes in the US District Court for the Northern District of California.

Technical methods of scraping

The lawsuit relies on what it describes as leaked source code from Suno to prove how the data was gathered. According to the filing, Suno allegedly used proxy services from Bright Data to rotate IP addresses and evade rate limits. This allowed the company to scrape millions of songs and lyrics from platforms like YouTube Music, Deezer, and Genius.

Reservoir specifically points to a technique called "stream ripping" to bypass YouTube's protections. They claim Suno used tools like YT-DL and YT-DLP to circumvent a "rolling cipher," which is a periodically changing algorithm that encrypts hidden file URLs. This process allows the AI to access the underlying audio files that are otherwise protected from external access.

The complaint also highlights a "stem splitting" workflow within the leaked code. This technology separates a full recording into individual tracks for vocals, drums, and instruments. Reservoir alleges that Suno deliberately sought out a cappella versions of songs to improve how its model generates lyrics and vocal performances.

How the AI models music

The filing argues that Suno's technology is built to model after pre-existing works rather than creating music from scratch. It cites a video by Suno's CEO, Mikey Shulman, who stated that the models are taught to continue a piece of music. Reservoir interprets this as an admission that the AI relies on existing data to generate three-minute songs from a simple idea.

The lawsuit also examines how Suno handles specific artist prompts and user uploads. While the platform currently blocks direct prompts for some famous names, it reportedly accepts misspellings to produce music in those styles. Additionally, Suno's terms grant the company a perpetual license to train on any audio files that users upload to the platform.

The complaint describes a specific test where a prompt for a "Miles Davis like" track resulted in two outputs named "Blue Note Quartet." Reservoir characterizes these as unlicensed derivative works. They argue that the model's ability to mimic specific styles and structures is a direct result of its training on the copyrighted works it allegedly copied.

The scale of Suno's growth

Suno has seen rapid growth since its version 3 became widely available in early 2024. By late 2025, the company reported that users were generating approximately 7 million songs per day. The platform has reached a scale where it now serves over 100 million people, including more than 2 million paid subscribers.

The company's financial trajectory is significant, with annual revenue projected to reach $1 billion. In June 2026, Suno closed a Series D funding round, raising over $400 million at a valuation of $5.4 billion. These figures underscore the commercial importance of the tool and the potential impact of the legal challenges it faces.

The legal battle is part of a broader trend of music publishers seeking to protect their catalogs from AI ingestion. If Reservoir succeeds, it could force AI music tools to establish formal licensing agreements. This would change the landscape for anyone using these tools to create commercial content like ads or soundtracks.