San Francisco-based Loudr® (http://loudr.fm) builds products and services that help content creators, aggregators, and music services identify rights holders, secure mechanical licenses, and pay royalties to music publishers. Powered by technology that parses publishing metadata and matches sound recordings to compositions, Loudr makes it easy for builders and creators to ...
Loudr is rolling out a new version of its API, the company’s latest step in advancing the once quiet music-business niche of mechanical licensing. The new version adds features that will make it even easier to find, manage, and link musical compositions and their owners. It even calculates royalties for clients based on their specific parameters, automatically.
It’s part of a larger effort to change the way licensing gets done in the U.S. Since compliance with specific copyright regulations is at the heart of compulsory licensing, digital mechanicals have proven difficult to manage at scale. The challenges of digital licensing are often complexified by the absence of comprehensive data and a means of coherently assembling from multiple data sources. Loudr has solved the problem by applying cutting-edge tech tools to the business processes the company developed when it got its start manually securing cover-song licenses for a cappella groups.
“Loudr's operational process combines knowledgeable human experts with a robust technology platform,” says Jesse Buddington, Loudr’s Director of Licensing. “The music licensing process has a great number of moving parts with multiple, branching steps, but is ultimately programmable with the right guidance. Our platform simultaneously learns from and augments our research team's efforts, allowing us to process an ever-increasing number of data points at an impressive degree of accuracy.”
That specificity is a major improvement over past practices, and offers a true alternative to current haphazard approaches to licensing, be it mass NOIs or other attempts to bury the problem of data matching, royalty administration, and licenses for digital music.
“Our systems are equipped to take in and process sensitive client data, and make the necessary calculations to generate a rate for each interactive streaming offering,” explains Loudr General Counsel Annie Lin. “This is similar to what other companies in the space do, except that Loudr's API offers much more transparency to the client as to what goes into the calculation.” Clients of Loudr’s API, which include CD Baby, Zebralution, and DistroKid, range from major indie distributors to music service platforms with large catalogs.
Loudr also manages the flood of data that has inundated music services, connecting the dots programmatically via its machine learning-powered data matching solutions (i.e. connecting compositions to recordings en masse). “We have data -- a lot of it -- and we've built a system to not only pull together the disparate pieces of music ownership data, but also a system to intelligently parse, categorize, and organize that data so that it can be presented back to our clients as structured metadata,” Lin continues. “By structured metadata, we mean data that is immediately actionable and can be used to inform the distribution process or power music-related user experiences, for example, products that let consumers ask ‘who wrote that song?’”
“We're taking a different pathway,” Buddington notes. “The ethos is making the connection quickly and in a scalable way to help our clients make the most of the information.”
About Loudr
San Francisco-based Loudr® (loudr.fm) builds products and services that help content creators, aggregators, and music services identify rights holders, secure mechanical licenses, and pay royalties to music publishers. Powered by technology that parses publishing metadata and matches sound recordings to compositions, Loudr makes it easy for builders and creators to secure music rights clearance and report royalties at scale. To date, the company has distributed over $1 million in royalties to songwriters and music publishers worldwide.