Invest in Moats,
Not Markets
A high-conviction portfolio of 25 businesses with durable competitive advantages, scored systematically across moat strength, growth trajectory, and live valuation. Built to compound wealth in the AI era — not just track it.
25
Portfolio Holdings
60+
Stocks Analyzed
≥ 75
Score Required
10%
Max Position Weight
The Thesis
Economic Moats Compound
The best businesses become harder to compete with over time — not easier. Pricing power, switching costs, and network effects strengthen as the business scales, delivering above-market returns on capital for decades.
AI Rewrites the Playbook
Most competitive advantages are AI-vulnerable: interfaces, talent scarcity, and embedded business logic can all be automated. We weight proprietary data, regulatory lock-in, and network effects 60% more heavily — the moats AI cannot replicate.
Concentration Beats Diversification
Owning 500 companies means funding mediocrity at scale. 25 high-conviction positions, each earning its place by scoring ≥75/100, concentrate capital where it compounds fastest.
The Scoring Framework
Computed from 10 individually-weighted moat types. Resilient moats total 60%, vulnerable 40%. Breadth bonus up to +4 pts.
Estimated 3-5 year revenue CAGR with named adjustments:
Price vs. scenario targets with live price feeds:
The 10 Moat Model
Every business is scored across 10 specific competitive advantages. Not all moats are equal in the AI era — five are AI-resilient (60% of the score, individually weighted by durability) because AI cannot easily replicate or destroy them, while five are AI-vulnerable (40%, individually weighted by disruption risk) because intelligent agents can increasingly substitute for them. Each moat is rated strong (100) · intact (75) · weakened (50) · destroyed (10), and a breadth bonus of +1 to +4 rewards businesses defended by more applicable moats.
Network Effects
Value compounds with every new participant
Following Metcalfe's Law, value scales with the square of participants. Every new user makes the network more valuable for all existing users, creating a self-reinforcing growth loop that competitors must overcome at the same scale — an enormous structural disadvantage for any challenger.
Proprietary Data
Private, compounding data flywheels
Data that accumulates privately over time and cannot be purchased or replicated by competitors. The longer the company operates, the harder it becomes to catch up. Think HealthKit biometrics, Palantir's classified government data, or Visa's transaction graph.
System of Record
The authoritative source of truth for critical decisions
The company's data store is the canonical reference that all downstream systems defer to. Replacing it requires migrating years of historical data and retraining every workflow built on top of it. Errors are catastrophic — so customers never voluntarily leave.
Regulatory Lock-In
Government licences, certifications & mandates
Advantages granted or protected by law: FDA approvals, financial licences, index inclusion, spectrum rights, or government contracts. These cannot be automated away and create near-permanent barriers because the certification process itself is the moat.
Transaction Embedding
Sitting inside the payment layer of operations
The business is embedded directly in the financial or operational flow of every transaction. Removing it requires rebuilding critical infrastructure, not just switching a preference. This creates extreme switching costs tied to real money movement, not just convenience.
Business Logic
Embedded operational workflows
The software encodes years of accumulated business rules, edge cases, and customisations that employees rely on daily. While this creates significant switching costs today, AI can increasingly model and reproduce business logic, gradually eroding the cost of migration.
Bundling
Value created by combining complementary products
Multiple products packaged together create convenience and cross-sell revenue that individual point solutions cannot easily match. AI-driven software commoditises features rapidly, making it easier for focused challengers to replicate any single element of the bundle at a fraction of the price.
Learned Interfaces
Fluency built through years of UI habit
Users invest time mastering a specific interface — keyboard shortcuts, mental models, workflows — making switching costly even when alternatives are technically superior. AI agents increasingly abstract away the interface layer, letting users command outcomes without learning a specific UI.
Talent Scarcity
Rare human expertise as competitive advantage
The business depends on recruiting and retaining a small pool of specialists — chip designers, quant researchers, elite engineers — whose skills are hard to find and expensive to poach. AI augments and in some domains replaces highly skilled human work, compressing the scarcity premium over time.
Public Data Access
Privileged access to publicly available information
The company has a head-start aggregating, structuring, or distributing data that is technically public but expensive to compile. AI web-crawlers and large language models rapidly close this gap by training on the same underlying data sources, compressing the advantage over time.
Each moat is rated strong (100) · intact (75) · weakened (50) · destroyed (10). Scores are weighted by moat type — resilient group totals 60, vulnerable 40 — with N/A moats excluded and weight redistributed within the group. A breadth bonus of +1 to +4 rewards businesses with more applicable moats. The result is the fully-computed Moat Score (40% of composite).
Common Questions
Ready to explore the portfolio?
View the current 25-stock allocation, explore all 60+ analyzed assets, or dive into individual company reports with moat scores, scenarios, and live valuations.