Sistava

Market Sizing and Validation

AI Finance Team

TAM, SAM, SOM analyses backed by real data, not whiteboard guesses

Your AI market-sizing team builds TAM/SAM/SOM analyses from primary data: industry reports, government statistics, competitor disclosures, and bottoms-up build-ups.,Top-down and bottoms-up methodologies cross-checked. Every assumption footnoted. Every number defensible in a board meeting.,New-market validation goes deeper: customer interviews synthesized, competitive landscape mapped, regulatory hurdles flagged.

Benefits

How It Works

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At a Glance

2
Methodologies triangulated per market
50+
Sources cited per analysis
Hours
From brief to first draft
100%
Citations on every number

When TAM Math Fails Boardrooms

The most common cap-raise killer is a TAM that doesn't survive scrutiny: numbers from one source, no bottoms-up reconciliation, no competition layer. Your AI market-sizing team builds the analysis that survives the board, the partner meeting, and the DD process — because the methodology is in the room with the number.

FAQ

Are these the kind of TAM numbers VCs trust?

Yes — methodology-driven, citation-heavy, with the dissenting view documented. The opposite of "consultant TAM" pulled from one slide.

How does it handle nascent markets?

It uses adjacent-market proxies, customer-interview synthesis, and forward-projection from current adoption curves. Every assumption explicit.

Can it size international markets?

Yes — country-by-country, with local-data sources where available and proxies where not.

What about regulatory and demand validation?

New-market validation includes a regulatory landscape review and a demand check via customer interviews or analog markets.