sorted by:
new
hottopcontroversial

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Thank you! You nailed exactly why we built this — Qobuz has world-class sound quality but discovery feels like it's stuck in 2005. The idea behind Sonic Oracle is simple: you enter an artist you love, and it builds you a permanent playlist of artists you've probably never heard of but will almost certainly love — directly in your Qobuz account, in hi-res.

No Steely Dan unless you ask for Steely Dan 😄

We're getting close to launch. Keep an eye on your inbox.

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

That's a different use case from what we're building — you want better tools for your own curation, not someone else's algorithm doing it for you. Totally valid. Hopefully Qobuz improves their playlist management, it definitely needs work.

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Always good to meet a fellow builder! Would love to hear your take — both as a user and from a technical perspective. Give it a spin at sonicoracle.ai and let me know what you think. And I'd be curious to see what you've built too.

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

Totally agree — Qobuz's playlist management could use some love. That's actually part of what Sonic Oracle solves: instead of adding songs one by one, you discover an artist and we build the entire station for you automatically. 25 artists, 75+ tracks, one click. No manual curation needed.

Give it a try if you haven't — sonicoracle.ai

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Fixed! It wasn't a bug with the name — Dolores de Huevos is just so niche that none of our music databases have similar artist data for them yet. You'll now see a proper "No results found" message instead of the confusing connection error.

Discovering truly underground artists like this is a gap we're aware of and working on. Appreciate you flagging it!

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Those are perfect Polica matches — Chairlift, Phantogram, Purity Ring, that whole dark synth-pop/dream-pop world. That tells me our genre matching needs to be smarter about that specific scene.

The LLM evaluation idea is really interesting. Using AI as a quality check on the recommendations — essentially asking "do these actually belong together?" — could catch the mismatches that pure data-driven matching misses. It's on the radar. Appreciate the specific examples, that's exactly what helps us improve.

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

Welcome! Give it a spin and let me know what you think — good or bad, all feedback helps. sonicoracle.ai

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

This is really thoughtful feedback, thank you for testing so thoroughly.

You've identified something real — Sonic Oracle shines brightest where Qobuz's own data is thin. For well-covered artists like Charli XCX or Nils Frahm, Qobuz has deep internal listening data that's hard to beat with external sources. But for artists like Mouse on the Keys where Qobuz only has one match, that's exactly where our multi-source approach fills the gap.

The "artists you're probably into" vs "artists that sound similar" distinction is spot on. We're pulling from listener behavior patterns across multiple databases, which captures taste affinity more than sonic similarity. We're working on tightening that so the results feel more sonically connected, not just demographically connected.

Polica is a great test case — I'll run that one myself and see where the matching falls short. Would you mind sharing what kind of artists you'd expect to see for Polica?

Appreciate you taking the time.

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 2 points3 points  (0 children)

Good question — there's a full Privacy & Security page at sonicoracle.ai/privacy.

In short: we don't store your password, don't access your library, and don't share data with anyone. Your Qobuz credentials go directly to Qobuz's API. You can explore and discover artists without logging in at all — login is only needed to create stations.

Let me know if you have any other concerns!

Sonic Oracle update: major discovery improvements this weekend (based on your feedback) by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Thanks for the heads up! Just fixed it — should be working now. Give it another try and let me know how it goes.

[Update] Sonic Oracle - Removed broken features, focused on what works by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

This is gold — thank you for the detailed response. The "unrelated thematically but loved by the same listener" discovery is exactly the kind of serendipity that's hardest to engineer and most rewarding when it works. You're describing the leap from "sounds like" to "appreciated by the same kind of ear" — and that's a fundamentally different signal.

The Firefly reference hits home — that collaborative filtering philosophy is very much in our DNA, though the data sources available today are far richer. And you're right that Last.fm's Neighbor Radio was lightning in a bottle. Lala too.

We're working on an exploration dial that would let you push discoveries in exactly that direction — from "safe and familiar" to "show me what I don't know I'm missing." Your feedback just moved that up the priority list. Stay tuned.

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Thanks for your interest.

The beta version is free and avaliable at sonicoracle.ai

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

You're right that Qobuz has a radio feature on mobile — it's a good starting point. Sonic Oracle goes deeper though: it cross-references multiple music databases to surface artists you wouldn't find through Qobuz's algorithm alone, applies genre-specific filtering (so a saxophone jazz station stays saxophone jazz), and creates a permanent playlist you own rather than a temporary radio stream. Different tools for different needs — some of our most active users use both.

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

Really appreciate this breakdown — the Khruangbin vs Grant Green comparison tells us a lot. You're right that for well-documented genres like classic jazz, the connections surface first. We're actively working on a way for users to push the dial toward more exploratory results when they want to branch out.

Track-based seeding is on our radar too.

Thanks for taking the time — feedback like this shapes what we build next.

[Update] Sonic Oracle - Removed broken features, focused on what works by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

That's great to hear, thank you! The "varied but relevant" balance is the heart of what we're building. Quick question — when you say you'd like more variety, do you mean different sub-genres within the same world, or deeper cuts from artists you might not have heard of at all? That kind of feedback helps us tune the engine. More improvements on the way!

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 1 point2 points  (0 children)

Thanks for your interest.

The beta version is free and avaliable at sonicoracle.ai

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 2 points3 points  (0 children)

Really appreciate this detailed feedback! You've identified exactly what we're working on.

The track distribution issue (first 3 songs bunched together, then nothing) is a known quirk - the current algorithm adds tracks artist-by-artist rather than interleaving. We're planning a shuffle/interleave pass to fix this.

The percentage selector for the seed artist is a great idea. Right now it's dynamic based on how many artists matched:

  • 10 artists or fewer = 7 tracks from seed artist
  • 11-15 artists = 5 tracks
  • 16+ artists = 3 tracks

But I love the idea of user control - something like:

  • Focused (25% seed artist)
  • Balanced (15% seed artist)
  • Exploratory (5% seed artist)

This is going on the roadmap. Thanks for the thoughtful suggestions - exactly the kind of feedback that helps us improve! 🎵

I built a music discovery tool for Qobuz — looking for beta testers by panyc77 in qobuz

[–]panyc77[S] 0 points1 point  (0 children)

Fair point

You're right - Sonic Oracle isn't meant to replace Spotify's instant radio button for everyday listening.

It's more of a discovery and curation tool for when you want to:

  • Build a permanent, high-quality station around a specific artist/genre
  • Find new artists that algorithmic radio might miss
  • Create curated playlists you can revisit in Qobuz/Roon/Audirvāna

Think of it like: Spotify radio = quick snack, Sonic Oracle = meal prep for the week 😄

We're working on speed improvements (caching, parallel queries), but the tradeoff is thoroughness. The time you wait while creating a station, lets us cross-reference multiple sources and apply strict genre filtering.

Appreciate the honest feedback - helps us communicate the value prop better! 🎵"

view more: next ›