Startup valuation calculators are systematically biased towards optimism. Their datasets are built on companies that successfully secured funding, excluding the vast majority that did not. This means the resulting valuations reflect only the "winners," creating an inflated perception of worth.
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The current fundraising environment is the most binary in recent memory. Startups with the "right" narrative—AI-native, elite incubator pedigree, explosive growth—get funded easily. Companies with solid but non-hype metrics, like classic SaaS growers, are finding it nearly impossible to raise capital. The middle market has vanished.
Acknowledging venture capital's power-law returns makes winner-picking nearly impossible. Vested's quantitative model doesn't try. Instead, it identifies the top quintile of all startups to create a high-potential "pond." The strategy is then to achieve broad diversification within this pre-qualified group, ensuring they capture the eventual outliers.
Founders are consistently and universally wrong about their financial projections, particularly cash runway. AI tools can provide an objective, data-driven forecast based on trailing growth, correcting for inherent founder optimism and preventing critical miscalculations.
Aggregate venture capital investment figures are misleading. The market is becoming bimodal: a handful of elite AI companies absorb a disproportionate share of capital, while the vast majority of other startups, including 900+ unicorns, face a tougher fundraising and exit environment.
The venture capital return model has shifted so dramatically that even some multi-billion-dollar exits are insufficient. This forces VCs to screen for 'immortal' founders capable of building $10B+ companies from inception, making traditionally solid businesses run by 'mortal founders' increasingly uninvestable by top funds.
Beyond outright fraud, startups often misrepresent financial health in subtle ways. Common examples include classifying trial revenue as ARR or recognizing contracts that have "out for convenience" clauses. These gray-area distinctions can drastically inflate a company's perceived stability and mislead investors.
This provides a simple but powerful framework for venture investing. For companies in markets with demonstrably huge TAMs (e.g., AI coding), valuation is secondary to backing the winner. For markets with a more uncertain or constrained TAM (e.g., vertical SaaS), traditional valuation discipline and entry price matter significantly.
Vested sources a differentiated data set by analyzing private company performance through state and local tax and labor filings. While the absolute numbers are often inaccurate for any given company, they are consistently inaccurate. Therefore, the trend line provides a reliable and valuable signal for a company's growth or decline.
The majority of venture capital funds fail to return capital, with a 60% loss-making base rate. This highlights that VC is a power-law-driven asset class. The key to success is not picking consistently good funds, but ensuring access to the tiny fraction of funds that generate extraordinary, outlier returns.
An ex-SoftBank investor observes that founder financial models have become more like marketing assets to sell a narrative than realistic planning tools. This systemic issue forces VCs to apply automatic 50-75% "haircuts" to projections, eroding trust and making the fundraising process highly inefficient for both parties.