VANKA PRE-SEED SELECtION CRITERIA
Exactly what Vanka AI evaluates for investment decisions.
Your Investment Score (0-100+)
The AI calculates your Investment Score across four weighted dimensions. Scores of 70+ qualify for consideration. The highest score each month wins funding.
Dimension 1: Founder Quality (30%)
What we evaluate:
Years of relevant industry experience
Previous startup experience and outcomes
Domain expertise and credentials
Vanka platform engagement depth
Speed of hitting milestones
Quality of AI interactions in your business planning
Full-time vs. part-time commitment
Team composition (solo founder vs. co-founders)
Example strength: "Former marketing executive with 8 years in the industry, used 5+ Vanka modules to plan business, achieved first customer within 45 days of incorporation."
Dimension 2: Market Opportunity (25%)
What we evaluate:
Total addressable market size and growth rate
Market timing and trend alignment
Competitive landscape and your differentiation
Customer acquisition viability
Sales cycle length
Regulatory environment
Example strength: "Entering a $500M market growing 15% annually, with clear differentiation from legacy competitors and efficient CAC model validated by early customers."
Dimension 3: Business Viability (25%)
What we evaluate:
Gross margin and path to profitability
Customer payback period
Revenue model clarity and validation
Scalability of operations
Automation potential
Capital requirements to reach profitability
Progress per dollar spent
Example strength: "SaaS model with 80% gross margins, 8-month CAC payback, can reach profitability with <$150k total capital, highly automatable with AI."
Dimension 4: Vanka Fit (20%)
What we evaluate:
Number of Vanka modules you actively use
Depth of integration with the platform
AI-first operational approach
Case study potential (compelling story, good communicator)
Alignment with "post-employment economy" thesis
Quality of operational data you can provide
Reporting infrastructure
Example strength: "Using 6 Vanka modules daily, built entire business on AI-first principles, compelling founder story about leaving corporate job to build AI-native business."
Expected ROI: The Real Selection Metric
Your Investment Score qualifies you (need 70+), but Expected ROI determines selection priority.
After calculating your Investment Score, the AI models the probability-weighted returns:
10x+ exit probability (based on your scores + sector base rates)
3-10x exit probability
1-3x exit probability
Loss probability
Expected ROI Formula:
Expected ROI = (P(10x+) × 1000%) + (P(3-10x) × 500%) + (P(1-3x) × 150%) - (P(Loss) × 100%)Example:
Investment Score: 87
P(10x+) = 8% | P(3-10x) = 20% | P(1-3x) = 30% | P(Loss) = 42%
Expected ROI = (0.08 × 1000%) + (0.20 × 500%) + (0.30 × 150%) - (0.42 × 100%) = 183%
The AI ranks all qualified applicants by Expected ROI. The highest Expected ROI typically gets selected—unless Extraordinary AI judgment applies (see below).
Bonus Factors
Social Media Amplification (Up to 1.15x multiplier)
100k+ engaged followers = 1.15x multiplier on final score
50k-100k engaged followers = 1.10x multiplier
10k-50k engaged followers = 1.05x multiplier
Re-Applicant Persistence (Up to +10 bonus points)
Second application with improvement = +3 points
Third+ application with continued improvement = +5 points
Consistent high-quality applications = +2 points per month (max +10)
Extraordinary AI Judgment: Beyond the Numbers
The highest Investment Score doesn't always win.
While the scoring system provides structure and objectivity, investing ultimately requires judgment. The AI has authority to exercise investor judgment in two scenarios:
Tie-Breaking: When two or more applicants have similar Expected ROI scores, the AI evaluates intangible factors:
Founder authenticity and communication style (from your video)
Narrative coherence and strategic clarity
Market timing that makes this moment uniquely important
Founder-market fit that's extraordinarily compelling
Contrarian Overrides (<10% of selections): In rare cases, the AI may select a lower-ranked applicant when it identifies:
Exceptional founder qualities not fully captured by the rubric
Unique strategic value to Vanka's mission ("post-employment economy")
Market timing considerations that create outsized opportunity
Domain expertise so rare it suggests unfair advantage
Example: An applicant ranked #3 with an 84 Investment Score might be selected over #1 with 89 if they're a former CTO at a unicorn in the exact space they're now targeting, and two major competitors just exited creating a consolidation window. The scores don't capture that perfect storm of timing + expertise.
All overrides are publicly documented. If the AI doesn't pick the highest score, we explain exactly why in the monthly selection announcement. Transparency applies to judgment calls too.
Philosophy: The algorithm prevents bias and ensures baseline quality. Judgment captures patterns too subtle for rubrics. Both matter.
What We Don't Consider
The AI is explicitly designed to ignore:
Your age, gender, race, or ethnicity
Where you went to school
Where you live (beyond market relevance)
Who you know in the industry
Previous employer brand names
Whether you can pitch well in person
Only measurable business fundamentals and platform usage matter.