LabelOS
AI Operating Model for Independent Music Labels
Independent labels are losing time to fragmented tools, manual workflows, scattered data, and reactive decision-making. LabelOS brings strategy, systems, intelligence, and AI fluency into one operating model designed for modern label teams.
What independent labels actually deal with
These aren't hypothetical problems. They came directly from working with independent labels on how they run.
Your release plan is rebuilt from scratch every time.
A full day of one person's work. Per release. Every release.
A systemised release workflow that runs the same way every time — with the intelligence already built in.
DSP data gets checked and then disappears.
It lives in Spotify for Artists. Nowhere else. Decisions get made from memory.
Streaming data captured automatically, centralised, and surfaced when decisions need to be made.
Marketing spend is half data, half instinct.
You know it should be more data-driven. Velocity thresholds exist in your head, not in a system.
Clear trigger logic: when to push, when to hold, when to scale — based on actual performance signals.
Data collection and contracts slow every release.
You're chasing metadata from others. Data entry once you have it. Contracts sitting in email threads.
Collection automated at the source. Contracts templated. Releases no longer sit waiting on admin.
Creator tracking is still manual.
Who posted. What they drove. What worked. All still being entered by hand, if it's tracked at all.
A creator intelligence layer — contacts, performance context, and campaign history in one place.
Copyright monitoring happens when it's already too late.
You find out when something goes viral that sounds like yours. Reactive, painful, and time-consuming.
Systematic monitoring that flags potential issues before they become disputes.
Four problems. Four systems.
Each one grounded in how labels actually lose time and leverage, built to stay running long after we leave.
From a full day to two hours.
Every release cycle started the same way, rebuilding the plan from scratch, chasing metadata, manually pulling DSP data. Now it's templated, automated, and running before you open your laptop.
Build your operating model →Built — not just promised
LabelOS ships with a purpose-built software layer. Your release cycle runs inside it from day one.
Release Manager
Every release in one place — status, countdown, task progress, cover art, and release notes.
Artist Roster
Artist profiles with streaming performance, revenue, ROI, and social links across every release.
DSP Analytics
Import streams and revenue from Spotify, Apple Music, YouTube, Amazon, and TikTok. One view across your whole catalogue.
AI Release Plans
Template-driven plans generated in seconds. AI insights explain the structure. Tasks auto-dated from release day.
Task Management
Assignees, due dates, overdue alerts, and weekly digest emails. Your team always knows what's next.
Calendar View
Monthly calendar showing every release date and task deadline across your whole roster.
Shareable Reports
Generate a read-only link for artists and partners. They see plan progress, streaming data, and campaign milestones.
Label Reports
Monthly stream trends, release comparison charts, campaign ROI, and full CSV export. The report builds itself.
Sync & Licensing
Track every placement from first pitch to signed deal. Log fees, territories, and status across TV, film, advertising, and gaming.
Playlist Pitching
Log every editorial and curator pitch across Spotify, Apple Music, Amazon, YouTube, and TikTok. Track status and estimated reach.
Physical Release
Record format details, chart position, units sold, and pressing quantities for vinyl, CD, cassette, and box set releases.
CRM & Pipeline
Track sync pitches, brand deals, and partnerships through a Kanban pipeline. Contacts, touchpoints, and live DSP metrics in one place.
A label operating system, not a toolbox
Four integrated layers — built to work together, not bolted on top of each other.
Navigator
AI Strategy
Where your operating model takes shape.
We map where your label is losing time and leverage — release planning, A&R, marketing decisions, team coordination. Then we build the operating model that fixes it. Structured, specific, and grounded in how your label actually works.
Forge
AI Systems
Where release intelligence is built.
We build the systems that make your release cycle repeatable — automated data collection, DSP intelligence, creator tracking, contract workflows, and marketing trigger logic. Everything connected. Nothing rebuilt from scratch.
Guide
AI Fluency
Where your team learns to operate natively.
Your team gets more done with less drag — not by working harder, but by working inside a system that handles the low-level operational weight. We build the fluency so it sticks long after we're done.
Velocity
AI R&D Lab
Where the frontier gets explored.
For labels ready to push further — AI-assisted A&R signals, content production systems, predictive release intelligence. We prototype fast and build what actually works for your catalogue and audience.
What your label
looks like
This is what labels tell us they're working toward. It's specific, it's achievable, and it's the basis for everything we build.
Your team is in creative mode, not admin mode.
The low-level operational weight — data collection, entry, chasing, templating — is handled by the system. Your people are focused on what they're actually good at.
Every release runs the same structured way.
Release plans don't get rebuilt from scratch. DSP data doesn't disappear after you check it. Marketing decisions have logic behind them, not just instinct.
You know what's working — and why.
Campaign post-mortems happen. Creator performance is tracked. Streaming signals inform decisions. You're operating on intelligence, not gut feel.
Your productivity tools actually work together.
Agents, calendars, content systems — integrated and running. Your team isn't switching between five tools to get one thing done.
Structured from day one — operational from day two
Discover
We map your label's current state — releases, tools, workflows, and friction points — through a structured intake that surfaces exactly what's costing you time and leverage.
Scope
We build a bespoke operating model blueprint — specific to your label, your catalogue, your team. Structured and ready to act on.
Build
We implement the systems and intelligence layers — moving fast without breaking what already works in your release cycle.
Scale
The operating model becomes infrastructure, not a project. Your team owns it. The time savings compound with every release.
Explore LabelOS.
Build your operating model.
Answer 5 questions about your label, your releases, and where you're losing time. We'll map your AI operating model — specific, structured, and ready to act on.
Takes 5 minutes · Free · No account required