Wiki-as-a-Data Platform - DAO

Veriscope DAO
(A decentralised autonomous organisation for knowledge governance, licensing, and revenue sharing.)

Mission

To build and govern a global, structured, licensed knowledge base for AI where contributors, curators, and developers are automatically rewarded based on the value they create.

Core Principles

  1. Transparency – All revenue, expenses, and payouts are on-chain.

  2. Meritocracy – Rewards are proportional to contributions and usage.

  3. Decentralised Governance – Stakeholders vote on policies, pricing, and licensing rules.

  4. Sustainable Growth – Treasury funds R&D, marketing, and community incentives.

DAO Organisational Structure

1. Token Model

  • $VRS (Veriscope Token) – ERC-20 governance & reward token.

  • Minted as:

    • Reward for contributors based on usage of their content.

    • Compensation for governance participation (proposals, votes).

    • Incentives for curators and developers improving the platform.

  • Token utility:

    • Voting power in DAO governance.

    • Staking to access premium API tiers at discounted rates.

    • Staking to unlock contributor licensing payouts.

2. Roles in the DAO

Automatic Compensation Model

Revenue Sources:

  • API subscriptions

  • Dataset licensing fees

  • Marketplace transaction fees

  • White-label deployments

Smart Contract Allocation (example percentages, adjustable via governance):

  1. Contributor Rewards Pool – 50%

    • Auto-splits by Usage Weight:

      • API retrieval logs determine which content chunks were used.

      • Licensing contracts log dataset IDs sold.

      • Each chunk/dataset has an owner/contributor ID → smart contract auto-distributes ETH/stablecoins.

  2. Curator Pool – 10%

    • Distributed to active curators who validated changes in the current cycle.

  3. Development Fund – 15%

    • Used for platform upgrades, paid via DAO proposals.

  4. Treasury Reserve – 15%

    • Held for future investment, liquidity, and emergencies.

  5. Governance Rewards Pool – 10%

    • Distributed to active voters and proposal creators.

On-Chain Process Flow

  1. Revenue Capture:

    • All customer payments (API, licensing, marketplace) go through a DAO-controlled multi-sig wallet or payment gateway that triggers on-chain revenue deposits.

  2. Attribution Tracking:

    • Every API call logs content_id and contributor_id in a public ledger (IPFS + blockchain).

    • Licensing deals include dataset IDs linked to contributors.

  3. Payout Calculation:

    • Smart contract reads usage logs and calculates the proportion of revenue each contributor earned.

    • Adjustments for curators and governance pools.

  4. Automatic Distribution:

    • Once per epoch (e.g., monthly), contract disburses ETH/stablecoins or $VRS tokens directly to wallets.

Governance Mechanics

  • Voting: Token-weighted voting with quadratic weighting for fairness.

  • Proposals: Require a minimum stake to prevent spam.

  • Key Governance Areas:

    • Adjust revenue split percentages.

    • Approve major licensing deals.

    • Fund partnerships, marketing, and integrations.

    • Add/remove curators.

    • Approve schema changes and new ontologies.

Treasury Management

  • DAO treasury held in multi-sig wallet with smart contract rules.

  • Automatic allocations on each revenue inflow.

  • Treasury health and expenditure reports visible in a public dashboard.

  • Optionally invest idle funds in DeFi yield strategies (with governance approval).

Example Smart Contract Allocation Pseudocode

Why This DAO Model Works for Veriscope

  • Aligns incentives — Contributors want high usage; curators want quality; developers want better retrieval performance.

  • Scales globally — Any expert can join, contribute, and earn without needing direct employment.

  • Compliant monetisation — Licensing contracts and contributor agreements link on-chain payouts with legal IP rights.

  • Auditable trust layer — All payouts and allocations are transparent, preventing disputes.

Here’s a monetisation strategy for Veriscope – Wiki-as-a-Data-Platform, designed to generate multiple defensible revenue streams while scaling both contributors and enterprise adoption.

1. Core Revenue Streams

A. B2B SaaS Subscriptions (Primary recurring revenue)

  • Audience: Enterprises, AI startups, and research institutions needing ongoing access to curated, structured knowledge.

  • Pricing Model:

    • API Access – Pay per call / per monthly usage tier.

    • Seats – User-based pricing for editorial and governance tools.

    • Storage & Indexing – Tiered by GB/TB of data indexed.

  • Tiers:

    • Developer – $99/mo for API sandbox & limited dataset access.

    • Pro – $1,000–$5,000/mo for private spaces, hybrid retrieval, and API credits.

    • Enterprise – Custom contracts with dedicated support, SLA guarantees, and on-prem/cloud deployment.

B. Data Licensing to LLM Vendors (High-margin “wholesale” deals)

  • Audience: OpenAI, Anthropic, Google DeepMind, Cohere, Mistral, etc.

  • Model:

    • Per-dataset licensing (one-off fees or annual subscriptions).

    • Exclusive licensing options at premium rates.

    • Revenue share with contributors whose data is licensed.

  • Examples:

    • $100K–$500K/year for exclusive datasets in niche verticals (e.g., biotech research, legal case law, industry standards).

    • $10K–$50K/year for non-exclusive rights.

C. Marketplace for Domain Wikis (Platform + transaction fees)

  • Audience: Subject matter experts, industry associations, content publishers.

  • Model:

    • Experts create niche domain wikis using Veriscope infrastructure.

    • Contributors set access/licensing terms.

    • Veriscope takes a 20–30% platform fee on transactions.

  • Upsell: Offer curation, governance, and licensing sales services for an additional cut.

D. White-Label Deployments

  • Audience: Enterprises needing a private, branded version of Veriscope for internal use or resale.

  • Pricing:

    • One-time setup fee + annual license (e.g., $50K–$250K/year).

    • Optional managed service add-ons (hosting, indexing, model integration).

2. Add-On Revenue Streams

A. Premium Retrieval & AI Features

  • Advanced reranking models, knowledge graph reasoning, and fine-tuned retrieval pipelines.

  • Premium fee for running inference-heavy retrieval augmentation.

B. Evaluation & Benchmarking Tools

  • Offer RAG evaluation dashboards, faithfulness scoring, and domain-specific retrieval benchmarks as a paid service.

C. Data Enrichment Services

  • Veriscope ingests client-provided data, cleans it, enriches with external sources, and structures it for AI.

  • Charged as a professional services line (hourly/day rate).

D. Contributor Monetisation Programs

  • Contributors can earn a % of licensing revenue from their content.

  • Encourages high-quality submissions and industry experts to join the platform.

3. Pricing Levers for Expansion

  • Volume discounts for API usage and data licensing.

  • Bundled offerings: e.g., RAG API + Fine-tuning datasets + Marketplace access.

  • Vertical-specific packages with tailored ontologies and retrieval optimisations.

  • Partnership bundles with LLM providers, vector DBs, and enterprise AI integrators.

4. Monetisation Flywheel

  1. Contributors add structured knowledge →

  2. Platform enhances with ontology, indexing, and governance →

  3. Developers & Enterprises use APIs for RAG →

  4. LLM Vendors license datasets →

  5. Revenue funds contributor rewards →

  6. More contributions improve data quality →

  7. Better datasets drive higher-value licensing deals.

DAO, WikiFrancesca Tabor