Research, Analysis & Thought Leadership
Data-driven insights from the intersection of AI, evaluation methodology, and the startup ecosystem. Research that matters for founders, mentors, and investors.
Featured Research
Our most impactful analysis and investigations into what makes startups succeed or fail.
Why 73% of Startups Fail Before Product-Market Fit: A Multi-Framework Analysis
We analyzed 15,000+ evaluations to understand the most common validation failures that kill startups before they find traction. Our research reveals that 68% of failed startups had addressable blind spots that structured evaluation would have surfaced. We break down the 5 most common failure patterns and show how framework-based analysis reduces early-stage mortality by up to 40%.
The AI Evaluation Revolution in Venture Capital: 2026 State of the Market
How multi-model AI is transforming deal screening, due diligence, and portfolio intelligence for institutional investors. We surveyed 200+ VCs and found that firms using structured AI evaluation tools report 3x faster deal screening, 25% better deal quality, and significantly reduced cognitive bias in investment committees. This report maps the emerging landscape and identifies the key capabilities that differentiate leaders.
Research & Analysis Library
Deep dives into evaluation methodology, market dynamics, and the tools shaping the venture ecosystem.
Framework Selection: Matching Methodology to Startup Stage
A practical guide to choosing the right evaluation frameworks based on startup stage (pre-idea, pre-revenue, growth), industry vertical, and strategic objectives. Includes decision matrix and case examples.
Building Investor Confidence Through Structured Validation
Data showing how founders with structured evaluation reports raise 3x more efficiently than those without. Analysis of 2,000 fundraising outcomes correlated with evaluation scores.
The Blue Ocean vs. Red Ocean Scoring Methodology
How VentureMerit differentiates between competitive and uncontested market opportunities. A deep dive into our dual-analysis approach and how it changes strategic recommendations.
Mentor Impact Measurement: From Anecdotal to Data-Driven
How accelerator programs are quantifying mentorship impact using evaluation intelligence platforms. Case studies from 5 accelerators with measurable outcome improvements.
Unit Economics Analysis: The Framework That Predicts Scale
Deep dive into how our unit economics framework evaluates CAC, LTV, payback periods, and margin structures. Includes benchmarks across 12 industry verticals.
Cognitive Bias in Investment Decisions: How AI Helps
Research on 15 documented cognitive biases that affect venture investment decisions and how multi-model AI evaluation reduces their impact on deal screening.
TAM/SAM/SOM: The Most Misunderstood Framework
Why most founders get market sizing wrong and how our AI validates bottom-up vs. top-down estimates. Practical examples of market sizing done right.
Cross-Cultural Startup Evaluation: Adapting Frameworks for Global Markets
How evaluation frameworks need to account for market maturity, cultural factors, and regulatory environments across different geographies.