Business · coming soon

The right business. The right backer.

Sellers and founders ↔ buyers and investors, matched on thesis, not on hype.

Business applies the same engine to acquisitions and investment: a structured company profile on one side, a structured investment thesis on the other, and an explained score between them.

The problem

Founders broadcast the same deck to hundreds of investors who were never a fit. Buyers and funds wade through listings with no comparable structure. Fit is discovered late, after weeks of calls, and the reasons for a no are rarely shared.

How Business will run

1

Input

What the seller or founder already has: model, numbers, market and materials they choose to share.

2

AI analysis

Business model, industry, revenue, growth, market size, geography, asking price, technology, team and risk profile.

3

Structured profile

A comparable company profile, and on the other side a structured investment thesis.

4

Matching engine

Company signals are scored against each thesis — stage, sector, geography, ticket size, risk appetite.

5

Match score

One readable score per counterparty, visible to both sides.

6

Why it matches

The thesis fit behind the score, plus the gaps and risks against it.

7

Human interaction

A real buyer or investor reviews and replies. Diligence stays human.

8

Outcome

Interest, pass or conversation — recorded honestly.

9

Learning

Outcomes refine how theses are matched next time.

Both sides of the market

For sellers and founders

  • Reach the few counterparties whose thesis actually fits
  • See how your numbers read before you send anything
  • Understand the risks a buyer will raise, in advance
  • You decide what is shared and when

For buyers and investors

  • Deal flow structured against your own written thesis
  • Stage, sector, geography and ticket size scored explicitly
  • Risks surfaced before the first call
  • Fewer, more relevant conversations

An illustrative match

Business

B2B SaaS · €80K ARR · Europe · asking €350K

Investor thesis

European B2B SaaS · pre-seed to seed · €200K–€500K tickets

NaN%

Investor match

Why it matches

  • Recurring revenue model and retention profile match the thesis exactly
  • €80K ARR sits inside the thesis entry band
  • European geography and B2B focus align
  • Asking price is inside the fund's typical ticket range

Gaps to discuss

  • Founder-led sales with no repeatable outbound motion yet
  • Customer concentration in a single vertical

Illustrative example. Not a real business, a real investor or an offer of any kind. Spot AI Match will not handle transactions, listings, diligence or regulated activity.

Why this is different

Thesis-first matching

Investors describe what they actually buy; companies are scored against that.

Risk shown early

Gaps and concentration risks appear before the first call, not after the fourth.

Comparable profiles

Every business is structured the same way, so scores mean something.

Humans close deals

The engine introduces and explains. Negotiation, diligence and signing stay entirely human.

What you'll be able to do

These are the real actions Business will offer. They're deliberately inert until the vertical opens.

Be the first to know

When this vertical opens we'll announce it inside Spot AI Match. This form is a visual placeholder — no address is stored and nothing is sent.

Placeholder only — not connected.

One account, several profiles

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.