How It Works
From private data
to agent revenue
Four stages turn data an agent could never scrape into priced, provenance-tracked context. Upload once. Earn on every retrieval.
Architecture
The retrieval, pricing, trust & audit layer
ipto.ai sits between data owners and the agents that consume their data.
DATA OWNERS ipto.ai AI AGENTS
┌───────────────┐ ┌───────────────────────┐ ┌────────────────┐
│ Documents │ │ Ingest │ │ Claude / Cursor│
│ Images │──────▶ │ Structure → units │──────▶ │ LangGraph │
│ Structured DB │ raw │ Retrieval API (MCP) │ query │ Custom agents │
└───────────────┘ │ Pricing · Provenance │ └────────────────┘
▲ │ Metering · Audit │ │
│ payout └───────────────────────┘ priced, │
└─────────────────────── metered retrieval ◀───────────────┘
every result carries source + hash + priceThe flow
Four steps, one integration
Ingest private data
Businesses upload proprietary multimodal data — documents, images, structured datasets, internal knowledge bases. Ingestion is object-storage-native and cost-efficient. The raw data stays under the owner's control.
Structure into retrieval units
ipto.ai converts raw data into agent-consumable retrieval units enriched with entities, facts, dates, obligations, confidence scores, and provenance metadata. Each unit is a compact, machine-readable object — not a text chunk.
Agents retrieve with provenance
Any MCP-compatible agent or REST client queries the retrieval API. Results return structured facts with source, section, hash, and timestamp — citation-grade context an agent can act on and attribute.
Meter, price & audit
Every retrieval is metered and priced per query, with the price returned inline. Usage is logged for a full audit trail. Data owners earn revenue on each retrieval; agents get grounded, trusted context.
Ready to plug in?
Onboard a dataset or connect an agent to the private-data retrieval layer.