Messy data, structured for agents: why we're building Fide

The Core Problem

Current AI memory works too much like search over static files. It can find chats and documents, but it does not really understand how information changes over time, why decisions were made, or which facts are now outdated. This results in agents confidently citing outdated policies, missing critical context from weeks ago, or making decisions without knowing what changed and why.

Even when supervised, agents miss context, rely on stale information, and make mistakes humans cannot easily audit. Humans operate within a fluid "world model" with temporal and causal context that AI agents lack today.

The Solution: Fide Context Protocol

We've designed the Fide Context Protocol, an open standard to turn messy data into a structured, time-aware graph that agents can actually reason across.

To turn simple file search into true digital memory, the protocol structures all incoming data around three questions:

What kind of thing is this?

The Fide Vocabulary classifies everything into explicit, typed entities — a person, an organization, an action, a concept, and so on.

What stable identifier points to it?

We assign a portable Fide ID so context from different apps and sources accumulates around the same real-world item over time.

What is being asserted?

We record statements about how things connect — capturing when a fact became true, the evidence and causality behind it, and what older information it superseded.

This solution isn't a better search tool; it's a shared and portable memory layer that gives AI agents a structured, evolving model of reality they can inspect and trust.

Join Us

At Fide, we're building the enterprise infrastructure that puts this protocol to work—making messy data structured for agents.

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