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Results as a Service

Which outcome is worth owning before you build?

This catalog is the demand map behind the vessel. It connects an operator's data footprint to class leaders already proving demand, RaaS gaps worth composing, and instruments that show whether the platform can deliver.

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Horizontal RaaS

Universal jobs: identity, billing, data, AI, workflow, telemetry, search, and trust.

Start here when the operator has a known data footprint.

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Vertical RaaS

Market wrappers: legal, construction, accounting, healthcare, restaurants, field work, PropTech.

Use it to decide which market should pay first.

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On-Chain RaaS

Trust jobs: wallets, attestation, DePIN registration, property tokenisation, settlement.

Use it when one fact must trigger many verifiable consequences.

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AI Organisations

Operating model: edge twins, agent passports, governed runtimes, learning loops.

Use it when the system must learn faster than competitors can copy it.

Class Leaders

Orientation markers, not endorsements: incumbents, AI-native alternatives, and outcome providers that show where demand is already moving.

Class

CRM

Traditional

Salesforce, HubSpot, Pipedrive

AI-native

Clay, Artisan, Relevance AI

Outcome

11x, Luna, Amplemarket

Class

AI + Intelligence

Traditional

IBM Watson, Google Vertex AI, AWS Bedrock

AI-native

Anthropic Claude, OpenAI, Mistral

Outcome

Cognition (Devin), Factory.ai, Augment Code

Class

Workflows + Automation

Traditional

Zapier, Make, n8n

AI-native

Gumloop, Lindy, Relay.app

Outcome

Bardeen, Cassidy, SuperAGI

Class

Analytics + Data

Traditional

Tableau, Looker, Mixpanel

AI-native

PostHog, Julius.ai, Hex

Outcome

Thoughtspot, Seek AI, Cohere Compass

Class

Search

Traditional

Algolia, Coveo, Elasticsearch

AI-native

Typesense, Weaviate, Pinecone

Outcome

Exa.ai, Perplexity, Vectara

Class

Blockchain

Traditional

Gap to research

AI-native

Sui, Ethereum, Solana

Outcome

thirdweb, Syndicate, Privy

DATA FOOTPRINT
  -> DEMAND REGISTER
    -> CLASS LEADERS
      -> CAPABILITY GAP
        -> INSTRUMENT
          -> LEVER
            -> VELOCITY

Use It​

  1. Map the operator's data footprint: invoices, jobs, contracts, conversations, assets, sensors, and compliance records.
  2. Read Horizontal RaaS to see which universal capabilities that footprint implies.
  3. Read Vertical RaaS to choose the market position where those capabilities matter most.
  4. Compare class leaders to separate commodity categories from outcome-provider gaps.
  5. Check Platform Instruments before claiming the capability is real.
  6. Pull Business Levers only when the instrument can read the result.
  7. Track Factory Velocity to see whether the bet is moving.

Scoring​

Every horizontal feature is scored on current capability, architecture fit, customer value, and edge against alternatives.

Priority = average current, fit, value, and edge multiplied by edge.

Edge is the multiplier. High-value commodities such as payments and auth can be rented or partnered when edge is low. High-edge capabilities such as multi-agent orchestration, smart contracts, and workflow learning loops compound when owned.

Demand Signals​

  • Multi-agent orchestration: priority 94.5, core status, Workflow Engine spec.
  • Smart contracts: priority 76, core status, Sui Wallet Safety spec.
  • Tokenomics: priority 76, active status, Sui Wallet Safety spec.
  • Knowledge management: priority 76, strong status, Agent Platform spec.
  • Process automation: priority 67.5, opportunity status, Intelligence Functions spec.
  • Document intelligence: priority 67, strong status, Intelligence Functions spec.
  • CI/CD automation: priority 67, strong status, developer tooling that compounds through Engineering.
  • API development: priority 67, strong status, Data Interface spec.
  • Audit logging: priority 60, strong status, Verification spec.
  • Customer support: priority 60, strong status, Intelligence Functions spec.

Suite Gaps​

Product research on integrated operations suites is a useful gap check for RaaS packaging. The strongest pattern is not more modules; it is horizontal functions bundled into vertical outcomes on one operational record.

Covered already: customer records, revenue workflows, delivery workflows, knowledge workflows, marketing telemetry, governance, and AI interface.

Under-specified: operational telemetry, workplace telemetry, evidence bundles, and device administration.

RaaS lesson: a platform becomes more defensible when every module enriches the same data footprint. The product boundary is not "CRM plus extras"; it is one operational record that can be repackaged by industry.

Critical Gaps​

  • Embedded payments: value 10; blocks all verticals; next step is a capability spec.
  • Identity/auth: value 10; every venture needs it; next step is decide build, rent, or partner.
  • IoT device telemetry: value 9; blocks field and physical-infrastructure plays; next step is DePIN infrastructure.
  • Resource booking: value 9; blocks workspace, field services, and asset scheduling; next step is a commerce gap spec.
  • Real-time events: high value; blocks live dashboards and agent comms; next step is live data capability.
  • Compliance framework: high value; blocks healthcare, finance, and sustainability; next step is extended verification.
  • Geospatial analytics: value 8; blocks smart-city and property intelligence; next step is a data-interface gap spec.

Allocation​

  • Core: own it. Spend most effort where edge is greater than 7: multi-agent orchestration, smart contracts, knowledge management.
  • Strategic: invest selectively. Build when it unlocks a vertical: compliance, APIs, DeFi, decentralised ID.
  • Opportunistic: partner or skip. Build only when demand pays first: communication, shipping, native mobile.

Failure Modes​

  • Treating class leaders as recommendations instead of evidence that a category has demand.
  • Copying a SaaS feature list without asking what data footprint the operator already owns.
  • Building low-edge commodity functions before proving a high-edge outcome gap.
  • Reading vessel velocity without checking whether the demand register justified the work.

Context​

  • Tight Five Loops — keep the catalog tied to intention, action, measurement, and learning.
  • Purpose — anchor the catalog to the operator's reason for choosing a capability.
  • Data Footprint — the operator asset this catalog reads.
  • Platform — the implementation layer where owned capability becomes reusable.
  • Build or Buy — decide what to rent, bridge, own, or defer.
  • Select Tech — evidence gates before choosing a tool or vendor.
  • AI-Native Edge Twin — prove one workflow before moving the core.

Zoom Out​

  • Up: Applications — the hub that frames software-selection decisions.
  • Across: Select Tech — run the evidence gates once the catalog identifies a gap worth filling.

Questions​

Which class leader is proving demand but leaving an outcome-provider gap?

  • Which category is commodity enough to rent, and which shapes the data model enough to own?
  • Which missing primitive blocks the highest-value data footprint from becoming a learning loop?
  • What instrument would prove this capability is real rather than claimed?