Corporate data,
made readable and verifiable by AI agents

Organizations can’t really influence what AI says about them. What they can do is provide AI with a structured set of corporate data that’s easy to discover and read. That is the core idea of Apparat: giving AI agents simple access to one authoritative dataset covering an organization’s relevant public information.

Machines live on a web built by humans, for humans. They answer from scattered pieces of information, in formats they can’t always read, and there is no way to tell whether an answer is drawn from a good source, a stale one, or none at all.

Apparat builds Data Fidelity Registers: a machine-readable data layer structured to be found, read and used by AI agents. Every fact is dated, linked to its source, and can be verified at any point, by anyone.

Want to know more? Learn how it works, read the frequently asked questions, or see the DFR specification. And if you’d like to start a conversation about your own register, do get in touch.