Groovian
Groovian provides a collaborative fraud intelligence network for the music industry, enabling distributors and DSPs to share anonymized banlists and screen incoming artists, releases, and accounts against collective data. The platform offers sub-second risk scores based on corroborated signals like device fingerprints and phone numbers, helping companies catch bad actors at intake before they cause financial damage. Currently in private beta, Groovian tracks eight fraud categories including artificial streaming, stolen content, and artist impersonation.
- Artificial Intelligence
- Data & Analytics
- Cybersecurity
- Financial Technology
- Music Technology
- Software Only
Funding
Founders
Product
Problem
Music distributors and DSPs maintain private banlists, forcing each company to independently rediscover the same fraudulent actors—whether through stolen releases, artificial streaming, or impersonation—after they've already been caught elsewhere. This fragmented approach costs money through DSP penalties, takedown processes, and wasted operational time, especially when fraudsters simply move to the next distributor with a new account.
Solution
Groovian creates a shared fraud intelligence network that turns private banlists into a collective defense system. When one organization flags a threat—such as a stolen master, fake stream ring, or impersonating artist—the rest of the network can automatically stop the same actor at intake, signup, or payout. The platform provides instant risk scores through a sub-second API call, with corroboration counts showing how many other distributors and DSPs have already flagged the same entity. Members gain day-one access to existing intelligence without needing to contribute first, and submissions remain anonymous, with identity values never leaving a company's environment in plaintext. This allows competing distributors to share threat data without exposing their own fraud investigation methods or customer files.
Target Audience
Primary customers are music distributors, DSPs, and labels that handle artist intake and content onboarding, particularly operations teams looking to reduce fraud-related costs and prevent repeat violations across their catalogs.
Features
- Sub-second API screening that returns JSON with risk score, severity level, and matching signals for auto-block, manual review, or acceptance workflows
- Entity matching across shared identifiers including device fingerprints, phone numbers, and signup IPs to connect aliases and uncover account farms
- Corroboration metrics showing how many member organizations have flagged the same artist, release, or account, building confidence in threat severity
- Anonymous intelligence sharing that protects submitting organizations' identities while still providing actionable signals to the network
- Bulk screening capability for 100+ records per request, enabling intake teams to check entire catalogs or artist rosters at once
- Cross-organization alert feed tracking eight fraud categories including artificial streaming, ISRC recycling, metadata laundering, and payment abuse
- Network feed with live match notifications showing threat levels, affected organizations, and fraud category for real-time awareness