Decionis

Execution pattern

Third-party data sharing

Decide what reaches an external system before the request is made.

Category
InfrastructureCommon in Healthcare · Fintech & payments · Public sector
Works through
aws · langchain · make · n8n +2 more
Proof
Signed Decision DossierVerifiable against our published JWKS.
Deploy
Shadow Mode firstMeasure on your own traffic before anything is stopped.

What executes

A workflow posts customer or business data to a webhook, an external API, or a vendor integration.

What normally goes wrong

Integrations are added for a narrow purpose and then reused for broader ones. The destination stays approved while the payload quietly widens, so the disclosure is a change in data rather than a change in configuration.

The decision

The signals available at the moment of the action, and the rule that judges them.

Signals

  • Destination and its approved purpose
  • Fields present in the payload
  • Data classification and residency constraints
  • Whether the recipient has a current agreement

The gate

Permit only the fields the destination was approved to receive, and refuse payloads carrying classifications the agreement does not cover.

ALLOW

The request proceeds with the approved payload.

ESCALATE

A widened payload waits on the data owner.

BLOCK

The request does not leave; the dossier records the fields withheld.

The Protocol — Deterministic. Contextual. Explainable.Four stages left to right. Input signals — user or agent identity, context and data, tools and resources, spend and budget, policies, history and reputation, and environment — enter the Decionis Protocol. Inside, the protocol normalizes context and intent, evaluates policies and rules, runs a deterministic risk and policy engine, and explains the reason and evidence. It emits a verdict: ALLOW (authorized), ESCALATE (needs approval or more info), or BLOCK (high risk or out of policy). The verdict drives an enforcement action: allow, block, require approval, or throttle and limit. Every decision is recorded for audit, learning, and continuous improvement.INPUT SIGNALSUser / Agent IdentityContext & DataTools / ResourcesSpend / BudgetPoliciesHistory & ReputationEnvironmentDECIONIS PROTOCOLNormalizeContext & IntentEvaluatePolicies & RulesRisk & Policy Engine(Deterministic)ExplainReason & EvidenceVERDICTALLOWAuthorizedESCALATENeeds approvalor more infoBLOCKHigh risk orout of policyACTIONSAllowBlockRequire ApprovalThrottle / Limit
Four stages left to right. Input signals — user or agent identity, context and data, tools and resources, spend and budget, policies, history and reputation, and environment — enter the Decionis Protocol. Inside, the protocol normalizes context and intent, evaluates policies and rules, runs a deterministic risk and policy engine, and explains the reason and evidence. It emits a verdict: ALLOW (authorized), ESCALATE (needs approval or more info), or BLOCK (high risk or out of policy). The verdict drives an enforcement action: allow, block, require approval, or throttle and limit. Every decision is recorded for audit, learning, and continuous improvement.

No policy pack decides this pattern yet

Write the gate above as your own policy: a repository policy file, or a bundle in your workspace.

Govern this pattern with a published Zap

Start from the workflow already running in your source system. Decionis adds the policy decision and returns signed evidence without turning Zapier into the authority.

Prove it, then deploy it

A verdict you cannot check is an opinion, and a gate you cannot measure first is a risk of its own.

View the signed proof

Every verdict on this pattern produces a Decision Dossier: the signals it saw, the policy version that judged them, and an Ed25519 signature anyone can check against our published JWKS — without an account, and without trusting us.

Deploy in Shadow Mode

Run this gate against your own traffic while it stops nothing. You get the verdicts it would have returned and the actions it would have held, so the decision to enforce is made on your numbers rather than ours.

What to do next

The same five steps for every pattern in the library.

  1. Simulate this recipe

    Run the policy against a realistic action in the browser. Push it past what the rules allow and watch the verdict come back. No account.

  2. View the signed Decision Dossier

    See exactly what was decided and why: the rule that fired, the evidence it read, the policy version in force, and an Ed25519 signature you can verify yourself.

  3. Deploy in shadow mode

    Measure what the policy would have caught on your own traffic without touching the live path. Every recipe defaults to shadow, so the first deployment carries no execution risk.

  4. Connect a real workflow

    Point the same policy at the system where the action actually originates — a checkout, an ERP posting, a Zap, an agent's tool call.

  5. Share the verified result

    Publish the proof: a public verification link, an embeddable badge, a PR comment, or an anonymized shadow-mode finding. This is how the next person discovers Decionis.

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