Scaling playlist production without growing headcount for a leading fitness audio platform.
A music intelligence and transition system that produces curated workout playlists at scale, replacing the human DJ bottleneck while preserving the curation standard the platform was known for.
THE CHALLENGE
A fast-growing fitness audio platform had built its reputation on expertly curated workout playlists with seamless DJ-style transitions. That reputation was also the constraint. As demand scaled, the manual curation process became a direct bottleneck on growth. Every new playlist required dedicated DJ time, which meant the content library could only expand as fast as the team could manually produce it. Adding volume meant adding headcount and cost at the same rate, a model that made scaling structurally impossible without either degrading quality or absorbing costs the business could not sustain.
OUR APPROACH
The challenge was not purely technical. It was about replicating something that felt inherently human: the instinct and timing of an experienced DJ, inside a system that needed to operate at a scale no human team could match. We approached this by first understanding what made the platform’s manually curated playlists work, then reverse-engineering those qualities into a system that could reproduce them consistently and automatically.
Rather than building a shuffle algorithm, we made the deliberate decision to model the cognitive logic behind music selection. The system needed to understand not just what tracks existed in the library, but how they related to each other in energy, flow, and transition quality. That decision made the build more complex but ensured the output would hold up against the standard users already expected.
- • Designing a music intelligence layer that evaluates tracks across tempo, energy, key, and genre to make curation decisions the way an experienced DJ would
- • Building a transition engine that generates natural, flow-preserving shifts between tracks rather than abrupt cuts or generic crossfades.
- • Architecting the system for scale from the outset so that adding thousands of new tracks would not degrade output quality or require manual reconfiguration.
- • Structuring the automation to run without human oversight on a per-playlist basis, removing the production bottleneck entirely.
THE RESULTS
Playlist production fully automated.
The platform moved from manually produced playlists requiring dedicated DJ time to a system that generates them continuously without human input across the entire active library.
Operational cost structure transformed.
The marginal cost of producing each playlist dropped to near zero, allowing the platform to expand its content offering without a corresponding increase in production spend.
Quality benchmark maintained at scale.
AI-generated playlist quality remained consistent with what had been produced manually, meeting the same transition and curation standard that had defined the platform’s reputation.
Library scalability unlocked.
The system handled large-scale music catalogs without degradation in output quality, removing the growth ceiling that had previously tied content expansion to headcount.
As the platform's content library continues to grow, it now does so on a cost curve that no longer moves in line with production volume. That structural shift is what makes this engagement significant beyond the immediate results.
A three-phase stabilization, subscription build, and cross-platform rebuild that moved a fragile inherited codebase to a stable, tested, and market-ready product with iOS and…
A cloud-based assessment delivery platform built from scratch in seven months, with multilingual support across five languages and an industry-first text notification feature, deployed…
An integrated AI recruitment platform spanning workforce intelligence, predictive analytics, sourcing, screening, and candidate engagement, translating a data-driven hiring vision into a functioning product…
Have a similar bottleneck
your team is hiring around?
Our senior team brings AI-native engineering capability that growing organizations cannot easily build internally at reasonable cost. We work in weeks, not quarters.