Fan decision intelligence
Stop guessing which single to lead with.
Opi gives you quantified fan intelligence before you commit your campaign budget, so you release the right track, to the right audience, at the right time.
The problem
The decisions that keep you up at night
Which track leads?
You have 15 tracks. Your gut says Track 3. Your A&R says Track 7. TikTok likes the snippet from Track 11. You're about to commit six figures to a campaign, and you have no structured way to know which track your fanbase will actually respond to.
The social-to-streaming gap
A sound blows up on TikTok. But streams don't follow. You've seen it happen: viral engagement that never converts. No tool tells you why the disconnect happens or which content will actually drive saves and streams.
Wrong bets are expensive
A misidentified lead single doesn't just underperform. It burns your release window, wastes marketing spend, and can set an artist back a full cycle. The cost of a wrong call on a $3M deal isn't theoretical. It's your quarterly target.
A better way
What if you could test a release strategy before spending a dollar?
Today, the closest thing to pre-release intelligence is an Instagram poll or a TikTok snippet test. One gives you stated preferences with no predictive value. The other costs $5K-$50K in paid promotion and only tests short-form engagement.
Opi is different. We simulate how your artist's actual fanbase will respond to each track before anything is released. You get a ranked recommendation with quantified confidence, so you know when to trust the signal and when to gather more data.
Fan decision intelligence, not polling, not engagement games.
How it works
Three steps to a smarter release
- 01
We ingest your artist's world
Genre, audience profile, streaming history, comparable artists, cultural positioning. Everything that shapes how fans will react.
- 02
We simulate your fanbase
Our AI generates a diverse synthetic fan population calibrated to your artist's actual audience, segmented by demographics, listening behavior, and fandom intensity. Each simulated fan evaluates your tracks the way a real listener would.
- 03
You get a decision-ready dashboard
Which track should lead. How confident the model is. Where fan segments disagree. When you need more signal before committing budget.
Validation
See it on a release you already know
We're running pilot programs with select labels and artist teams. Early partners will test the simulation on past releases they already know the outcome of.
Retrospective testing
Pilot partners test on catalog they trust. No campaign budget on the line until you've seen how the output reads against real outcomes.
Honest confidence
Every recommendation ships with confidence scores, so you know when to trust the signal and when to gather more data before committing spend.
A&R stays in the room
Opi augments judgment; it doesn't replace it. A structured second opinion for release planning, not a crystal ball.
Use cases
Built for the decisions you actually make
Lead single selection
"We had 12 tracks and two weeks to decide. The simulation flagged the track our A&R had ranked third, and it outperformed every other option in week-1 streams."
Release sequencing
Rank your full tracklist by predicted performance. Plan your single cadence, deluxe drops, and fan-community exclusives with data behind each choice.
Marketing budget allocation
Know which track deserves the campaign spend, and which ones will find their audience organically through algorithmic discovery.
Creative direction validation
An artist pivoting genres? Expanding into a new market? Test how the existing fanbase will respond before committing to a direction that could alienate your core audience.
Why Opi
What makes this different from what you already have
| A&R Intuition | Streaming dashboards | TikTok snippet tests | Instagram polls | Opi | |
|---|---|---|---|---|---|
| When | Pre-release | Post-release / real-time | 2-4 weeks pre-release | Pre-release | Pre-release |
| What it tells you | Gut feeling | What already happened | Short-form engagement only | Stated preference (biased) | Predicted fan response with confidence scores |
| Quantified? | No | Yes, but retrospective | Partially | No | Yes, with quantified confidence scores |
| Cost of being wrong | Your entire campaign budget | N/A (reactive) | $5K-$50K in promo spend | Free but unreliable | Subscription |
The industry has plenty of tools that tell you what happened. Opi tells you what's going to happen, with honest confidence intervals so you know exactly how much to trust it.
It gets smarter with every release
Opi's simulation works from day one with zero fan participation. But when you choose to, you can distribute a lightweight fan prediction game to your artist's audience. Every fan response calibrates the model, making future simulations more accurate. More artists, more fan data, better intelligence. You control the pace.
Who it's for
Built for your team
Marketing Directors
You own the campaign budget. You need to know which track justifies the spend before the invoices start. Opi gives you a data-backed recommendation to bring to the release planning meeting.
A&R
You trust your ears. So do we. Opi doesn't replace your judgment. It gives you a second opinion backed by simulated fan response data, so you can validate your instincts or catch a blind spot.
Managers & Indie Labels
You don't have a 50-person analytics team. You need tools that punch above their weight. Opi gives you enterprise-grade release intelligence at indie scale.
Early access
Join our pilot program
We're currently running pilot programs with select labels and artist teams. Early partners get hands-on access to the simulation for their next release, and help shape the product.
FAQ
Common questions
- We're validating the simulation through pilot programs and retrospective testing on past releases you already know the outcome of. Every recommendation includes confidence scores, so you know when to trust the signal and when to gather more data. We'd rather be honest about limits than overpromise.
- No. It's a decision-support layer. Think of it as a structured second opinion: quantified, transparent, and without a personal stake in any particular track.
- At minimum: the artist name and the set of candidate tracks. We pull public context (streaming history, audience demographics, comparable artists) automatically. If you share Spotify for Artists exports or internal audience data, the simulation gets even more precise.
- Those tools are excellent at tracking what's already happening: streams, chart positions, social engagement. Opi works before anything is released. We predict how fans will respond to tracks they haven't heard yet. Different problem, complementary to your existing stack.
- We don't need audio files. The simulation works with audio feature descriptors, lyrical themes, and production style metadata, not the actual recordings. Your unreleased music never leaves your hands.
How accurate is the simulation?
Does this replace A&R judgment?
What data do you need from us?
How is this different from Chartmetric / Luminate / Outlier?
What about unreleased music? Is my IP safe?
Your next release deserves better than a coin flip.
Join the waitlist for early access to our next pilot cohort. We're working with select labels and artist teams while we build.
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