Eclusia
Freemium
Legal professionals handling confidential cases
After an AI agent wires $2.4 million to a new account, the first question auditors ask is who approved this — and most AI governance stacks have no answer.
EMILIA sits as a control layer between an agent's decision and the system of record, blocking any irreversible write until a named human has signed off on the exact action hash from their own device. The protocol's core guarantees — no replay, no self-approval, no bypassing the gate — are machine-checked as TLA+ invariants and Alloy facts on every commit, not asserted in a policy document. Every approved or rejected action produces a Merkle-anchored evidence receipt retrievable at a standard API endpoint, so your auditor gets a signed artifact, not a log you assembled after the fact. The control layer is passive: it does not plan or execute anything itself, which means there is no agentic surface area to compromise.
Bottom line: Pick EMILIA when an AI agent touches money, credentials, or any write your org cannot reverse and needs a provable chain of custody — but if your AI workflows are read-only or the latency of a synchronous human gate breaks your throughput SLA, you are paying for accountability infrastructure you cannot use.
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Freemium
Legal professionals handling confidential cases
Free · Open source
AI security researchers
When an authenticated agent, not a hacker, quietly changes a payment destination or rotates a production credential through approved channels, the existing audit trail shows a legitimate action and no accountable owner. EMILIA addresses that gap by intercepting every high-risk write before it reaches the system of record, requiring verified actor identity, a policy-pinned action context, and a one-time nonce, then generating a signed, Merkle-anchored receipt that publicly verifiable tooling — vendor-published packages in JS, Python, and Go — can independently confirm. The workflow is: intercept, require proof, commit or block, issue receipt. Nothing commits without passing all three gates.
The differentiating feature is formal verification, not marketing copy about it. The vendor states that 26 TLA+ invariants and 35 Alloy facts are machine-checked by TLC on every commit. The published theorems cover properties that matter in practice: an authorization can be consumed exactly once and never replayed (ConsumeOnceSafety), a signoff is bound to the exact action it approved and nothing else (SignoffBindingMatch), and no actor can approve or contest its own action (SelfContestImpossible). These are bounded model-checks of the authorization state machine — the vendor is explicit that they prove the protocol, not any AI model’s behavior.
EMILIA fits enterprise AI deployments where agents handle wire transfers, beneficiary changes, production deployments, credential rotations, or any action that triggers SOX, financial compliance, or zero-trust policy review. Where it breaks: the protocol requires a synchronous human signoff before the action executes, so any workflow where throughput or latency cannot tolerate a human-in-the-decision-loop — high-frequency automated processing, for example — hits a structural wall that no configuration option resolves. Self-hosting is not available, which means teams operating in air-gapped or strict data-residency environments face a blocker before the first integration.
Integration surface includes a REST API with auditor-grade evidence packets at /api/v1/trust-receipts/{id}/evidence and a browser-based verifier. The specification is published under Apache 2.0, so compliance teams can read the formal proofs directly rather than accepting vendor attestations. A live demo and playground are available for teams that want to run a crash test before committing to a pilot.
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