If you're the type who digs deep into liner notes, follows obscure side projects, or gets excited about unexpected musical connections, you know the frustration.

We already know mainstream platforms excel at serving up familiar comfort zones based on our listening patterns. Streaming services are great for daily, effortless listening reccs.

But what about when you want to truly shift and expand your musical horizons and not just follow your own linear logic and inertia? Or when you want understand things like if/how Joni Mitchell influenced Radiohead's Kid A? Or trace the path from Can to Vampire Weekend? Those deeper musical relationships get lost in the noise of simplistic, synthetic, and short-term engagement-driven recommendation models.

Our hypothesis: traditional algorithmic paradigms often lead nowhere meaningful in the longer-term.

Our thesis: Stell-R. A musical genealogy toolkit to complement your regular streaming that helps you uncover the why behind the music you love:

• Puts you in control of your own musical discovery path: What are you really curious about? Choose your starting points.
• Trace the artistic lineages and influences that shaped your favorite artists.
• Discover the deep cuts and forgotten gems that bridge musical movements.
• Explore contextual connections: not just "should be like,," but "inspired by," "collaborated with," "emerged from", "sounds like,".
• Navigate music through artistic influence paths rather than marketing categories, popularity metrics, or even user-level correlates (although those last are cool, we agree).
• Find your next musical obsession through grounded links that honor musical history, artistic intention, and, we think, ultimately: your chances of truly expanding your musical universe
• No user data: just music

We are committed to transparency in how we handle visitor data:

• We do not store nor collect individual user data - we have no idea who you are (and that's OK!)
• We do not store nor collect individual user activity
• We collect and store IP addresses at session level
• We collect and store IP addresses at session level solely to assess broad geographical usage trends across sufficiently large regions
• All data is processed in aggregate (to the city level) form only
• Regional analytics help us understand our reach and audiences, and improve our platform accordingly
• We will never share any individual session data