Intent → Sourcing → Transformation → Serving
The process begins when an AI agent, developer, or system submits an intent—a high-level request for a specific type of data (e.g., “gameplay behavior during reaction-time events”).
TURF’s Intent-Orchestrator parses the request into filters like time range, content type, behavioral tags, and freshness needs.
From there, the orchestrator either:
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Matches the request with existing, clean data chunks in storage, or
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Calls on the Freshness Module to fetch new data from overlays, agents, or partner sources in real time or batches.
All incoming data is broken into chunks, sanitized, and linked to Decentralized Identifiers (DIDs). Each chunk gets a child DID tied to the contributor's parent DID, making attribution verifiable—but anonymous. The data is then delivered through the Data Egress Handler, completing the fulfillment loop.
Context Gathering & Fulfillment Intelligence
Each intent is broken into atomic parts—like metadata filters, time windows, preferred sources, and expected traits.
These help the orchestrator pinpoint the most relevant data chunks.
The Judge Module then scores how well those chunks match the original intent. This fulfillment score affects:
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What gets delivered
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How it's priced
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How rewards are distributed
This ensures data is not just accurate but also valued properly.
Data Transfer Programmability
TURF’s protocol is built to be modular, secure, and privacy-first. Key features include:
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Chunk-level metadata: Every data chunk carries tags, timestamps, origins, and history.
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DID attribution: Each chunk is tied to a source-specific DID chain.
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Sanitization layer: Ensures safe, usable data.
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Push/Pull support: Real-time and on-demand delivery models.
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ZK incentive claims: Contributors prove ownership with zero-knowledge proofs—no identity exposure.
This makes the system highly programmable for complex, agent-driven workflows.
Exchange Commerce
Every data delivery triggers a token-based transaction.
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Requesters pay in Turf tokens or stablecoins.
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A programmable split allocates part to the protocol and the rest to the data contributor.
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Contributors use zero-knowledge proofs to claim rewards—verifying their role without revealing who they are.
The system supports:
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Dynamic pricing based on quality and demand
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Transparent rewards
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Non-custodial, composable settlements
Contribution Mapping & Tracking
Each data chunk is cryptographically tied to the contributor through a child DID, under a parent DID.
This setup enables:
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Verifiable yet private attribution
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Full traceability across real-time and batch data sources
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Lifecycle tracking without compromising identity
It also supports advanced logging, scoring, and auditability.
ZK-Driven Privacy & Compliance (CCPA & GDPR)
Privacy is enforced from the ground up through zero-knowledge proofs and decentralized access controls.
TURF is compliant by design with major data regulations like CCPA and GDPR, enabling:
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Proof of ownership without identity exposure
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Contributor consent and opt-out controls
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Cryptographic guarantees of revocation, non-use, and selective disclosure
TURF makes it possible to share and monetize data in a way that’s programmable, privacy-first, and aligned with real-world regulations—empowering contributors without sacrificing control.