AI-powered matching for opportunities that matter.
Spot AI Match turns messy real-world inputs into structured profiles, scores the fit between two sides of a market, and explains why. People still make the decision.
Our central principle
The engine measures, ranks and explains. It never approves you, hires you, buys your business or adds you to a playlist. Every outcome is a human choice.
Explore
Music is live and working today. The other three are being built in the open — you can read exactly how each one will work.
Music
Your music. The right audience.
Independent artists get matched with real playlist curators and paid, written feedback. Consideration is what you pay for — placement is never for sale.
Work
Professionals ↔ opportunities.
Match real experience against real roles, with the factors and gaps spelled out on both sides.
Business
Businesses ↔ buyers and investors.
Match a business or project with the buyers and investors whose thesis actually fits it.
Promotion
Brands ↔ creators and audiences.
Match a product with the creators whose audience genuinely overlaps with it.
The shared flow
Whatever the market, the pipeline is identical. Only the inputs and the people at the end change.
1
Input
You provide what you actually have: a track, a CV, a business, a product.
2
AI analysis
The input is read, measured and normalised into comparable signals.
3
Structured profile
Loose material becomes a structured profile the engine can reason about.
4
Matching engine
Your profile is compared against the other side of the market.
5
Match score
A single readable score summarises the strength of the fit.
6
Why it matches
Every score is broken into the factors behind it — and the gaps against it.
7
Human interaction
A real person reviews, replies, accepts or declines. This step is never automated.
8
Outcome
The result is recorded honestly, positive or negative.
9
Learning
Outcomes feed back in so future matching gets sharper.
One engine
Genre fit, seniority fit, investor thesis fit and audience fit are the same mathematics with different inputs. Building it once means every vertical inherits the same explainability.
About tokens
In Music, one token buys one curator review — consideration and written feedback, whether the curator accepts or declines. Future verticals are expected to use a comparable consideration model, but nothing about the live Music token economy changes here.
See Music pricingWhat a match score is — and is not
A match score describes potential fit from the data we have. It is not a promise, a guarantee or a prediction of success. A high score means the conversation is worth having; the other side is still free to say no.
Your Spot AI Match account is the same across every vertical. Today it carries your live Music profile; Work, Business and Promotion profiles will attach to the same account when they open.