A programmable, privacy-preserving, and intent-driven engine that manages the entire data lifecycle.
Sourcing
Data enters the system through a flexible contribution interface, connecting overlays, agents, and data providers.
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All incoming data is broken down into smaller chunks and tagged with decentralized identifiers (DIDs) and optional metadata to keep it aligned with its context.
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These contributions can come in real-time (like overlays) or as batches (such as contracts, MCPs, or third-party providers).
Orchestration
The Data Ingress Handler takes the incoming data chunks and routes them through the pipeline.
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Once in, the data is sampled and sanitized to ensure it’s safe, consistent, and relevant for downstream use.
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A Freshness Module checks whether existing chunks are still valid or if they need to be fetched again in real time.
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Each data chunk is cryptographically tied to a child DID. A ZK Chunk Rights Prover allows for claims that are both verifiable and privacy-preserving.
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At the center, the Intent-Orchestrator reads requests from agents or developers and matches them with relevant data using contextual understanding.
At last, the Judge Module scores how well the served data matches the original intent. This score influences things like delivery, pricing, and rewards.
Utilization
Once processed, structured data feeds are delivered to the requesting agents—whether that’s LLMs, inference engines, or analytics systems.
- Payments are handled through tokenized transactions. A small programmable cut goes to the protocol, and the rest is claimable by the original data contributor.
Finally, contributors use zero-knowledge proofs to claim rewards—ensuring that attribution is verifiable, but their identity remains private.