THE PROBLEM Venture capital firms are increasingly tasked with evaluating startups at very early stages of development—often before these businesses have established track records, proven product-market fit, or validated financial performance. Traditional due diligence models, which rely heavily on historic data and financial statements, fall short in these cases. This creates several challenges: - Limited Evidence Base: Early-stage startups lack the operating history, audited financials, or reliable revenue patterns that typically anchor investment decisions. - Uncertain Market Validation: Products may still be in development, with untested customer adoption or limited sales data, making demand forecasts speculative. - High Noise-to-Signal Ratio: Founders’ narratives, pitch materials, and market projections often lack objective benchmarks, leaving investors vulnerable to over-optimism or bias. - Difficult Comparability: Without standardized metrics, it is challenging to compare opportunities across different industries, stages, or business models. As a result, VC firms face heightened risk when trying to identify which emerging ventures are truly investable versus those that may struggle to scale, sustain, or generate long-term returns.