Your stack
Three lines in the code you already ship
Node.js, Python, Go, Java or an MCP config — the gate drops in at the call site, not around your architecture. Copy the sample, keep your framework.
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Presence + Protocol
Deterministic execution control for AI agents & workflows.
Decionis Presence proves the human; Decionis Protocol evaluates the action against policy before execution, returning a cryptographically verifiable ALLOW, ESCALATE, or BLOCK decision.
p95 <120ms policy evaluationSigned, offline-verifiable proof
presence-gate.ts
$ npm install @decionis/sdk @decionis/presence-node// setup · gate = createDecionisExecutionClient({ authorityBaseUrl }) · presence = new PresenceClient({ baseUrl, apiKey }) · refund(human) → { request, execute: issueRefund }
const human = await presence.check(token, "refund.issue");
const run = await gate.enforceAndExecute(refund(human));
if (!run.executed) queueForApproval(run.decision);3 lines · prove the human → decide → execute
Browser sandbox · ephemeral WebAuthn credential + Ed25519 key · the liveness frame and everything else stay on this page. The ceremony saves a sandbox passkey on your device — delete it from your password manager any time. Full server-backed ceremony: presence.decionis.com/demo
Shipped execution surfaces
Node.jsPythonMCPGitHub ActionsZapierShopifyAWS LambdaServiceNowSAP
01 / Where it fits
Security · DevSecOps · Infra
Fail closed, with evidence
No verified decision, no execution: timeouts, invalid proof and an unreachable authority all deny. Every decision leaves a signed dossier you can verify offline, and rollout starts in read-only shadow mode.
Production behaviorAI agents · LLM apps
Agents propose. Policy decides.
Gate MCP tool calls and agent actions outside the model's discretion. ESCALATE routes the action to a verified human through Presence before anything executes.
How the boundary works02 / Policy as code
Your policy already exists. It just isn't executable yet.
Policy usually lives across PDFs, markdown, Jira, Confluence, XML, transaction logs, SAP notes and uploads. The draft flow turns those sources into a reviewed, versioned Decionis artifact — and every synthesized rule is validated through the real rules compiler. Anything that can't become an executable predicate is returned as a review item, never a silently broken rule.
Unstructured inputs
PDFJSONXMLMarkdownTransaction logsSAP notes
Live policy-source connectors
JiraConfluenceNotionGoogle DriveGit repositorySAP
The production draft flow
POST /v1/orgs/:orgId/policies/packs/draft
{
"sources": [{ "source_type": "upload", "label": "refund-authority-v3.pdf", … }],
"live_connector_ids": ["<jira_connector_uuid>"]
}
→ { "pack": { "rules": [ … ] }, "review": [ … ] }
// every rule validated by the rules compiler before it reaches yourefund-authority-v3.pdf · sources[] · source_type "upload" · text extracted server-side
ACME COMMERCE — REFUND AUTHORITY POLICY (excerpt, p.12)
4.2 Refunds at or below $500 may be issued automatically
by support tooling.
4.3 Refunds above $500 require named-approver sign-off
before execution.
4.4 Refunds above $10,000 are prohibited pending CFO
review this quarter.
4.5 Every refund decision must retain an auditable record
of the approving identity.Deterministic extraction · runs in this browser
Browser demo of the deterministic draft path on fixture documents · nothing leaves this page. Org-side drafting (LLM-assisted, same review model) validates every rule through the real rules compiler.
03 / Architecture
A decision boundary, not another agent framework.
Your model still reasons. Your tools still execute. Decionis sits between intent and effect, evaluates a versioned policy snapshot, and emits portable proof of the exact decision.
Explore the full architecture01 · Intent
Agent or workflow
Proposes an action.
02 · Decide
Decionis policy gate
Deterministic snapshot evaluation.
03 · Enforce
Execution boundary
Proceeds only on the resolved path.
ALLOW
Execute with a bound decision.
ESCALATE
Step up through Presence.
BLOCK
Stop before side effects.
Every path emits a Decision Dossier: intent hash, policy version, reason codes, outcome and Ed25519 proof.
04 / Production behavior
Know what happens when dependencies fail.
Latency, timeouts and fallback posture are part of the control—not implementation details to discover during an incident.
p95 <120ms
deterministic compute target
Strict enforcement
Fail closed for consequential mutations
Use bound or strict enforcement so REJECT, REVIEW, ESCALATE, invalid proof, timeout, or an unreachable authority never calls the action callback.
no verified grant → no executionShadow mode
Observe first, without changing behavior
The existing workflow continues while Decionis records the verdict it would have enforced. Promote policies only after reviewing real traffic and drift.
observe → compare → promoteHost boundary
Make fallback behavior explicit
Some host hooks own their timeout semantics. Keep the gate deadline inside the host deadline, or move enforcement to the API or network boundary you control.
timeout policy belongs in architecturePresence
Adaptive human verification for high-stakes escalations
When a policy returns ESCALATE, Presence evaluates behavior, device trust and liveness, then steps up the named human with passkey or out-of-band mobile approval before the action is released.
Zero-risk rollout
Start in read-only Shadow Mode.
Record policy drift and would-be verdicts on real workflow traffic before enforcing anything inline.