AI has created unprecedented demand for data. Capturing its value is the hard part.
Agents and humans need access to proprietary content, specialized datasets, organizational knowledge, and continuously updated information to do useful work. At the same time, the organizations that hold this data need greater control over how it is accessed, what can be done with it, and how they benefit when it creates value.
Both of those can be true at once. When access can be priced, scoped, and verified, data stops being something you protect by keeping it still and becomes something you can put to work: sold, licensed, evaluated, or exchanged with a partner, without ever handing over the underlying data, code, or model.
Monetize access
Charge for what your data does, not just for a copy of it. Price on your terms: per document, per query, per computation, or by subscription.
Control dataflows
Decide who gets in, what they are allowed to compute, and what is allowed to leave. The controls travel with the transaction instead of ending at the handoff.
Easy collaboration
Match, measure, and analyze against another organization’s data with neither side surrendering a copy, unlocking partnerships that stalled before they started.
To help organizations realize the value of their data for the growing AI economy, invocate provides low-friction infrastructure to control and monetize how humans and AI agents use data, built on over a decade of research in data systems, data markets, privacy, AI, and data ecosystems.
Data access is not a binary decision
Instead of share it or don’t, invocate lets you determine who can access a resource, what they can do with it, what they receive in return, and what information is released on structured or unstructured data, for humans or AI agents, with compensation through payment, reciprocal access, and more.
Publishers & Content Owners
Give AI agents paid access to articles, archives, data, or other proprietary content, charging per document, query, computation, or subscription.
Data Vendors
Let prospective customers or agents test a dataset against their own problem before purchasing it, without revealing the underlying data, evaluation code, or model.
Enterprises
Give employees and AI agents access to sensitive internal information while restricting what can be retrieved, computed, or shared downstream.
Partner Organizations
Collaborate or exchange information without requiring either party to surrender unrestricted copies of its assets.
Define the terms, run the transaction, prove what happened
1. Define
Set the conditions under which data may be used, what the evaluation is, and what is returned in exchange.
2. Transact
Computation takes place without unnecessarily transferring the underlying data, models, or code.
3. Verify
Only approved results are released, and the transaction produces auditable evidence of what happened.