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Buy or Build

Who owns your data—and what happens when you need to leave?

In the age of AI coding, the build option just got cheaper. But the real question isn't cost—it's sovereignty.

The Decision Matrix​

Two axes determine your choice:

                    DATA SOVEREIGNTY
                    Low ───────────► High
                   ┌────────────────┬────────────────┐
        Commodity  │     BUY        │   BUILD LATER  │
                   │  (SaaS OK)     │  (Own the data)│
STRATEGIC          ├────────────────┼────────────────┤
VALUE              │   HYBRID       │     BUILD      │
        Core       │ (Buy + Bridge) │  (Own it all)  │
                   └────────────────┴────────────────┘
QuadrantWhenExamples
BUYCommodity function, low data sensitivityEmail, calendar, basic CRM
BUILD LATERCommodity now, but data becomes strategicAnalytics, customer insights
HYBRIDCore function, need speed, plan to migrateMVP with SaaS, bridge to owned
BUILDStrategic function, high data sensitivityProprietary workflows, AI training data

The AI Impact​

AI coding changes the calculus:

FactorBefore AIWith AI
Build costHigh (months of dev time)Low (days to weeks)
MaintenanceFull team requiredAI-assisted updates
Speed to marketBuy winsBuild competitive
Data ownershipLocked in SaaSYours by default

But: AI doesn't eliminate complexity—it shifts it. Maintenance, security, and integration still require judgment.

The Crypto-Enabled Option​

What if there's a third path—neither pure SaaS nor pure build?

The Trust Stack Changes Everything​

Traditional SaaS: You generate data → they store it → you pay to access it → switching costs lock you in.

Crypto-enabled infrastructure inverts this:

PrimitiveTraditional SaaSCrypto-Enabled
Data SovereigntyVendor owns your dataYou own objects explicitly
TruthTrust the vendorVerify on-chain
IdentityPlatform credentialsPortable identity (zkLogin)
TrustInstitutional reputationCryptographic proof
PortabilityExport friction, lock-inOpen by default

The insight: You can BUY the workflow (SaaS UX) while OWNING the data (on-chain objects). Best of both worlds.

Data Flow Properties​

Before buying any tool, apply the Clean, Fast, Open test:

PropertyQuestionRed Flag
CleanSingle source of truth?Copy-paste between systems
FastReal-time sync?Batch jobs, overnight sync
OpenCan you export ALL data?Proprietary formats, no API

If you can't check all boxes, you're accepting lock-in risk.

The Framework​

Step 1: JTBD Analysis​

What job is the software doing for your business?

  • Functionality — What must it do?
  • Data Management — What data does it touch? Who needs access?
  • Simplicity — How easy to use/maintain?
  • Speed — How fast must it respond?

See Products for JTBD methodology.

Step 2: Evaluate Options​

QuestionBuyBuildCrypto-Enabled
Features match needs?Partial (generic)Exact (custom)Exact + portable
Total cost of ownership?Recurring + switchingUpfront + maintenanceUpfront + low switching
Time to value?FastSlow (faster with AI)Medium
Data ownership?VendorYouYou (verified)
Integration flexibility?LimitedFullProtocol-based

Step 3: Data Footprint Assessment​

Data is the new oil. Answer these:

  • Where do you collect unique data?
  • What processes generate valuable insights?
  • What domain secrets need protection?
  • Could this data train AI that competes with you?

If data is strategic, own it. If commodity, rent is fine.

Step 4: Industry Vertical Check​

Different industries have different sovereignty requirements:

VerticalData SensitivityRecommendation
HealthcareVery High (PII, PHI)Build or crypto-enabled
Real EstateHigh (transactions, valuations)Crypto-enabled ideal
FinanceVery High (regulated)Build with compliance
GamingMedium (player data)Crypto-native (NFTs)
Supply ChainHigh (provenance)DePIN infrastructure

See Vertical RaaS for industry-specific patterns.

The Hybrid Approach​

Most businesses shouldn't choose pure buy OR pure build. The hybrid path:

PHASE 1: Buy (Speed)
    ↓
    Use SaaS for fast market entry
    ↓
PHASE 2: Bridge (Data)
    ↓
    Export/sync data to owned infrastructure
    ↓
PHASE 3: Build (Control)
    ↓
    Replace commodity SaaS with owned systems
    ↓
PHASE 4: Crypto-Enable (Sovereignty)
    ↓
    On-chain objects, verifiable data, portable identity

Key insight: Start with speed, end with sovereignty. Plan the migration from day one.

In-House Development with AI​

If building, evaluate your AI capabilities:

AI Coding Maturity​

LevelCapabilityBuild Readiness
1Code completionLow—still need full team
2Function generationMedium—AI assists humans
3Feature developmentHigh—AI builds, humans review
4Autonomous agentsVery High—AI maintains itself

Costs and Timelines​

FactorTraditionalAI-AssistedAI-Native
Initial buildMonthsWeeksDays
MaintenanceTeamIndividual + AIAI + oversight
Iteration speedSlowMediumFast
Technical debtAccumulatesManagedAI-refactored

Risks​

  • AI may not deliver full functionality—have fallback
  • External dependencies (APIs, data) create fragility
  • Compliance of AI-generated code needs auditing
  • Model access and pricing can change

Decision Checklist​

Before deciding:

  • Is this function commodity or core to our differentiation?
  • Does this data train competitive AI models?
  • Can we export ALL data in standard formats?
  • What are switching costs if vendor fails/pivots?
  • Does our industry have special sovereignty requirements?
  • Can we bridge to crypto-enabled infrastructure later?
  • Do we have AI coding capability to build/maintain?

Innovators​

Context​

Decision Framework:

Data & Sovereignty:

Industry Patterns: