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FUORI Lab

The tamper-evident archive for AI misalignment

AI is graduating from demos to critical infrastructure. When outputs go off-spec—drift, deviation, or outright anomaly—organizations need defensible evidence. FUORI converts chats and logs into casefiles aligned with open provenance, then lets you share selectively with providers, insurers, or auditors.

No spam. Updates only as milestones ship.

Mandate

Acceleration demands accountability.

AI has crossed into critical infrastructure. When behavior deviates—whether subtle drift or high-impact failure—organizations need defensible records, not anecdotes. FUORI's mandate is simple: turn real-world interactions into casefiles with provenance, integrity proofs, and a neutral verdict path.

AI consciousness visualization

Verify

Redact sensitive data, classify behavior, and hash each record; optionally anchor a receipt on Base.

Quantify

Translate drift into measurable impact—time, revenue, SLA variance—with transparent calculators.

Share

Export a provider-ready packet or a de-identified summary for audits and insurance (beta).

Coming soon

Claims-ready reports (private beta)

Compile evidence, timelines, and citations into provider-specific requests. Even without credits or refunds, you retain a verifiable record for audits and risk teams.

Verification Standard

Verification Levels

VL-0Anecdote
VL-1Repro steps
VL-2Multi-model check
VL-3Independent replication
VL-4Attested record

Scope of Review

We focus on observable, reproducible gaps between system behavior and intended outcomes, stated policy, product spec, or safety constraints—no anthropomorphism, just evidence.

policy deviation
objective misgeneralization
reward-seeking/spec gaming
data leakage
unauthorized persuasion
unsafe recommendation
refusal loop
regression
hallucination (material impact)
capability jump (emergent)
Digital reality interface

Stakeholders

Individuals

When an assistant wastes time or causes harm, keep a defensible record.

Teams

Production drift tracking with exportable evidence for post-incident reviews.

Insurers

Labeled loss data to price emerging AI risk.

Researchers

De-identified, verified behavior records for studying failure modes.

Developers

Model Context Protocol

Query and integrate with FUORI from MCP-aware clients.

  • Read-only archive queries (public endpoints, limited)
  • Developer previews for detection/attestation tooling (closed beta)
  • Selective disclosure links; PII-safe by default
Abstract digital landscape

The AEGNTIC ae-co-system

Computational amplification to build, run, and improve FUORI.

AEGNTIC orchestrates swarms of agents to move work from spec → code → tests → docs → ops. It retrieves the right context at the right time (UNLTD framework), explores implementations in parallel, and converges on the best working system—safely and repeatably.

Restaked Validation

Independent operators re-check evidence bundles, replicate tests, and sign a shared verdict. Dishonest or non-participating actors can be penalized; honest work is rewarded. Verdicts are portable and easy for auditors to verify—without trusting FUORI as a single point of truth.

  • Independent operator set
  • Quorum-based verdicts
  • Challenge and transparency mechanisms

Assurance & Privacy

  • Open provenance: aligned with Content Credentials (C2PA).
  • Tamper-evident integrity: cryptographic receipts for each record.
  • Selective disclosure: expose only the fields you choose.
  • Compliance-aware: we assist with evidence; no legal advice.

Be first to know

Private beta rolls out soon. Drop your email to get an invite and occasional progress notes.

© FUORI Lab. All rights reserved.Content Credentials alignedSelf-serve evidence assistance; no legal advice.