AIality Infrastructure pilot
How it works

Sources become versioned, provable Reality.

AIality is not "AI that reads the web." It is a lifecycle: capture, verify, version, serve — with an explicit chain of custody attached to every exact state.

End-to-end flow

Sources(vendor policies, docs, APIs)
AIality Reality Core(capture · verify · classify · lock)
Versioned Reality(immutable FactStateVersions)
REST / MCP Gateway(authenticated)
Agents / Systems(resolve · lock · act)

The Reality trust stack

  1. 01
    Source
    A concrete, audited surface — a vendor's published policy page, API, or document.
  2. 02
    Observation
    Evidence is captured and stored immutably, ontology-agnostic enough to reprocess later.
  3. 03
    Verification
    Extraction proposes a CandidateFact. An LLM alone can never assign VERIFIED or high assurance.
  4. 04
    Immutable Reality
    A new FactStateVersion is appended — history is never rewritten, only extended.
  5. 05
    Authority
    An explicit, versioned binding of this state to the source surface that authorizes it.
  6. 06
    Freshness
    A frozen-at-creation horizon determines whether a state now reads FRESH or STALE.
  7. 07
    Change
    A deterministic classification of what changed between two exact states, and how.
  8. 08
    Impact
    Registered dependents are attributed against the change that affects them.
  9. 09
    Reality Lock
    An immutable decision basis an agent can act on — and later re-check.

How a Reality state ages, mechanically

Every exact state is immutable — a change never edits it, it supersedes it. This is the general mechanism, not a specific vendor's real history (see the homepage for that).

Illustrative lifecycle — not live data
  1. FSV 1
    Captured, verified, versioned — frozen forever once written.
  2. FSV 2
    A new observation supersedes it. History is preserved, never rewritten.
  3. FSV 3
    A future revalidation — not yet observed.
Why now

Agents need a Reality layer the same way networks needed DNS.

As agents take actions on behalf of people and organizations, "what did the source say, and when" stops being a nice-to-have footnote and becomes the thing an audit, a dispute, or a downstream decision depends on. That requires treating external facts as a first-class, versioned asset — not a cache that silently overwrites itself.

Why AIality, not…

The difference is the Reality lifecycle, not "AIality uses AI."

Search

Search finds documents. It does not track whether a specific fact within a document changed, nor preserve what it said historically.

RAG

RAG retrieves passages for a prompt. It has no concept of an immutable, versioned fact state, freshness, or authority over the source.

Scraping

A scrape is a snapshot with no lifecycle: no assurance level, no reprocessing discipline, no distinction between OBSERVED and VERIFIED.

Generic monitoring

Uptime/content-diff monitors detect that a page changed, not what changed semantically, nor whether the change affects a specific predicate an agent depends on.

LLM browsing

An LLM reading a live page at request time can misread it, and produces no durable, auditable record of what it saw.

Data aggregators

Aggregators compile current values. They do not preserve immutable publication history or bind history to a stable public identity.