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Layer 2 — The problem
Authority still lives in documents. Execution no longer waits for them.
AI can now execute real-world actions, but enterprises still express authority in documents, approvals and disconnected systems.
How the gap shows up
Four symptoms of the same underlying problem, in the order teams usually recognize them — first the thing you have watched happen, last the thing you are afraid of.
01
Authority lives in documents, not in the execution path
A policy that exists in a PDF, a spreadsheet or a Jira approval cannot stop the action it governs. By the time a human reads it, the order shipped, the payment cleared, the agent already called the tool.
02
Every system enforces its own rules, differently
The same authority — who may spend what, on whose behalf, up to which limit — is re-implemented in the storefront, the ERP, the ITSM queue and the agent framework. Four implementations, four drift rates, no single answer.
03
Autonomy removed the human pause
Approval workflows assumed a person between intent and execution. Agents close that gap to milliseconds, so the check has to move into the execution path itself or it does not happen at all.
04
After the fact, nobody can prove what was decided
Logs record what happened. They do not record which policy was in force, which version, on what evidence, or why the action was permitted — which is exactly what an auditor, a regulator or an incident review asks for.
The answer, in one sentence
Put the decision inside the execution path rather than beside it.
Before AI acts, Decionis decides.
An intent — from an AI, a user, or a system that wants to act — reaches Decision, where the Decionis Protocol evaluates the action. The evaluation returns one of three verdicts: ALLOW, meaning authorized; ESCALATE, meaning it needs approval or more information and is routed to whoever holds the authority; or BLOCK, meaning it is high risk or out of policy. An allowed action reaches Execution, where it is executed safely and recorded; an escalated action reaches it only once approved; a blocked action never does. Decionis is the neutral decision authority between intent and execution.
Nothing reaches execution without passing through the decision. That is the whole idea — everything else on this site is how it is done, where it runs, and how you can check that it is true. See all seven canonical diagrams.
How Decionis compares
Decionis overlaps with GRC suites, AI guardrail libraries, fraud tools and native platform rules without replacing any of them. Each comparison states the difference, the full matrix, and when the alternative is the better choice.
Decionis vs ServiceNow IRM
Integrated risk management on the ServiceNow platformDecionis gives your team an execution control plane before money moves or systems change. ServiceNow IRM is broader integrated risk management inside the ServiceNow ecosystem.
Read the full comparison →
Decionis vs ServiceNow IRM
Integrated risk management on the ServiceNow platformChoose Decionis when
Choose Decionis when your critical job is confidence before an action happens: a clear proceed, hold, or escalate recommendation with signed Decision Dossiers tied directly to the execution decision.
Choose ServiceNow IRM when
Choose ServiceNow IRM when you need a broad ServiceNow-native governance and risk program with deep workflow ownership inside that platform.
| Comparison area | Decionis | ServiceNow IRM |
|---|---|---|
| Primary job | Deterministic execution control before money moves | Broad integrated risk management inside ServiceNow |
| Best fit for | CFO, COO, risk, procurement, and operations leaders | ServiceNow platform owners and enterprise governance teams |
| Core artifact | Decision Dossier with policy checks and execution proof | Risk workflows, control programs, and platform records |
| Tradeoff | Narrower than a full IRM suite | Heavier platform footprint for execution-specific use cases |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Not the primary focus. ServiceNow IRM is broader governance and workflow administration rather than a narrow action gate before every downstream step. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Broader risk records and platform workflows rather than a portable per-decision dossier plus validation-pack model. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Can support workflow decisions, but not positioned around one confidence-scored execution verdict at the action boundary. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Can model broader governance workflow states, but deliberate hold logic is not the core positioning. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Broader governance posture rather than a focused before-money-moves execution layer. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can integrate in broad enterprise environments, but Google Cloud / Vertex AI governance fit is not the core positioning here. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Broader platform controls rather than explicit org-wide and per-decision kill switches as a primary public proof point. |
How is Decionis different from ServiceNow IRM?
ServiceNow IRM is designed for integrated risk management across a broad enterprise workflow estate. Decionis is narrower and more execution-focused: it sits between decision systems and execution systems as the control plane that gives your team an answer before actions occur.
Who is Decionis for in this comparison?
Decionis is for teams that already know the risky action path and need a deterministic execution gate in front of it, especially in finance, procurement, and operations.
Why would a CFO choose Decionis over ServiceNow IRM?
A CFO chooses Decionis when the priority is reducing preventable execution loss, proving why a transaction or approval happened, and moving faster than a platform-scale IRM rollout.
What are the tradeoffs?
Decionis is not a full enterprise workflow and GRC suite. If the main requirement is broad program management across many governance domains inside ServiceNow, ServiceNow IRM is broader. If the main requirement is a deterministic execution gate before money moves or system state changes, Decionis is more direct.
Decionis vs IBM OpenPages
Governance, risk, and compliance managementDecionis gives your team an execution control plane at the point of action before money moves or systems change. IBM OpenPages is broader governance, risk, and compliance software for enterprise risk programs.
Read the full comparison →
Decionis vs IBM OpenPages
Governance, risk, and compliance managementChoose Decionis when
Choose Decionis when you need deterministic execution control and faster proof of why an action happened before the system commits it.
Choose IBM OpenPages when
Choose IBM OpenPages when you need a broader GRC program system with enterprise-wide governance workflows and risk administration.
| Comparison area | Decionis | IBM OpenPages |
|---|---|---|
| Primary job | Enforce policy before execution | Manage governance, risk, and compliance programs |
| Speed to value | Focused quickstart and pilot path | Better for larger program rollouts |
| Decision artifact | Decision Dossier tied to execution | Broader GRC records and governance workflows |
| Tradeoff | Less broad than a full GRC suite | Broader but heavier for narrow execution control use cases |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | OpenPages is broader program governance, not primarily a real-time downstream action gate. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Broader GRC records and governance documentation rather than a portable Decision Dossier plus validation-pack model. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Not positioned around one confidence-scored execution verdict before action proceeds. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Can support broader governance and review states, but do-nothing or deliberate hold logic is not the core product posture. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Better for enterprise governance breadth than before-money-moves execution control. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can sit in large enterprise stacks, but Google Cloud / Vertex AI governance fit is not the primary differentiation. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Broader governance controls rather than explicit org-wide and per-decision kill switches as a product surface. |
How is Decionis different from IBM OpenPages?
IBM OpenPages is a broader GRC platform for managing governance and risk programs. Decionis is purpose-built for one narrower job: giving your team an execution control plane before approvals, routing, or spend are committed.
Why would a CFO choose Decionis over IBM OpenPages?
A CFO chooses Decionis when the main business case is execution safety, audit-grade justification, and rapid workflow control instead of a broader GRC transformation program.
How does setup compare?
Decionis can start with a quick diagnostic and move into a focused pilot. OpenPages is better suited when the organization is prepared for a larger GRC operating model.
What are the tradeoffs?
Decionis is not a full GRC operating system. If your requirement is broad risk inventory, program administration, and enterprise compliance workflows, OpenPages offers more breadth. If your requirement is pre-execution enforcement with signed audit artifacts, Decionis is the narrower and stronger fit.
Decionis vs Alloy
Identity and fraud prevention platform for financial institutions and fintechsAlloy focuses on identity, fraud, compliance, and credit decisioning for financial institutions. Decionis governs broader enterprise execution with deterministic policy gates before money moves or system state changes.
Read the full comparison →
Decionis vs Alloy
Identity and fraud prevention platform for financial institutions and fintechsChoose Decionis when
Choose Decionis when the main requirement is deterministic pre-execution control over spend, approvals, routing, and other high-stakes operational or financial actions.
Choose Alloy when
Choose Alloy when the main requirement is identity, fraud, AML, onboarding, or credit decisioning inside financial-services workflows.
| Comparison area | Decionis | Alloy |
|---|---|---|
| Primary job | Policy-gated execution before operational or financial action | Identity, fraud, compliance, and credit decisioning for financial services |
| Best fit for | CFO, COO, procurement, risk, and operations leaders | Fraud, compliance, onboarding, and fintech risk teams |
| Core artifact | Decision Dossier with policy proof and execution accountability | Identity and fraud workflows with configurable risk decisions |
| Tradeoff | Not an identity-verification or fraud-orchestration platform | Not a general enterprise execution control plane |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Strong inside identity, fraud, and financial-services decisioning, but not a general execution gate for enterprise operational actions. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Focused on identity and fraud decision workflows rather than portable Decision Dossiers and org-level validation packs. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Strong for risk decisions in its domain, but not positioned as one cloud-agnostic certified verdict for broad enterprise execution. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Domain workflows can defer or challenge decisions, but deliberate hold logic for general enterprise execution is not the primary story. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Works in financial-services risk flows, but not as a general before-money-moves execution control plane across procurement and operations. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can integrate into cloud stacks, but Google Cloud / Vertex AI governance preservation is not the central positioning. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Operational controls exist in-domain, but org-wide and per-decision kill switches are not the main public execution-control proof. |
How is Decionis different from Alloy?
Alloy is built for identity and fraud prevention, onboarding, monitoring, and credit decisioning in financial services. Decionis is built to govern whether a business action should execute at all under institutional policy, with one enforceable verdict: execute, block, escalate, or deliberately hold action across finance, procurement, risk, operations, and AI-driven workflows.
Who is Decionis for in this comparison?
Decionis is for enterprise teams in finance, procurement, risk, and operations that need deterministic control over approvals, spending, routing, and workflow execution. Alloy is stronger when identity risk and fraud operations are the center of gravity.
Can Decionis and Alloy coexist?
Yes. Alloy can govern identity and fraud risk inside customer lifecycle flows, while Decionis can govern downstream operational and financial execution where enterprise policy, auditability, and kill-switch control still matter.
Why would a CFO choose Decionis over Alloy?
A CFO chooses Decionis when the risk sits in execution itself: purchase approvals, payment release, vendor actions, workflow routing, or other business actions that need deterministic control before value moves.
Decionis vs Guardrails AI
Developer tooling for AI validation and guardrailsGuardrails AI helps developers constrain and validate model behavior. Decionis gives your team an execution control plane for enterprise actions, with deterministic policy checks and signed Decision Dossiers.
Read the full comparison →
Decionis vs Guardrails AI
Developer tooling for AI validation and guardrailsChoose Decionis when
Choose Decionis when your business problem is confidence before a high-stakes action proceeds, not only model validation.
Choose Guardrails AI when
Choose Guardrails AI when the immediate need is developer control over model inputs, outputs, and validation flows.
| Comparison area | Decionis | Guardrails AI |
|---|---|---|
| Primary job | Control business execution with policy gates | Validate and constrain AI model behavior |
| Best fit for | Finance, operations, procurement, and risk leaders | Developers and ML platform teams |
| Core artifact | Decision Dossier and execution proof | Validation rules and structured output checks |
| Tradeoff | Less developer-SDK oriented | Not designed as a business execution control plane |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Not the primary job. Guardrails AI focuses on model validation and output control, not downstream business execution gating. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Validation rules and model controls rather than Decision Dossiers and audit-ready validation packs for high-stakes business action. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Model validation and structured outputs, not one confidence-scored certified execution verdict. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Can block or constrain model behavior, but deliberate do-nothing logic for business execution is outside the main product job. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Not positioned around before-money-moves execution control for finance, procurement, or operations. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can be used in AI stacks, including Google Cloud, but not as the execution control plane that preserves approvals and Decision Dossiers. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Model and application controls instead of org-wide and per-decision execution kill switches. |
How is Decionis different from Guardrails AI?
Guardrails AI focuses on developer-layer validation around model behavior. Decionis operates at the business execution layer, where policy, accountability, financial consequences, and system state changes matter.
Who is Decionis for in this comparison?
Decionis is for operators, finance teams, procurement leaders, and risk owners who need an execution control plane around the action that follows an AI suggestion.
What are the tradeoffs?
Decionis is not a replacement for developer guardrail tooling around every model call. Teams building agent systems may still use both.
Why would a CFO choose Decionis?
A CFO cares less about model syntax validation and more about whether a decision can execute without violating policy or creating loss. That is Decionis' core job.
Decionis vs Lakera
AI security for protecting generative AI applicationsLakera is positioned around AI security and protecting GenAI systems. Decionis gives your team an execution control plane for enterprise decisions before money moves or systems change.
Read the full comparison →
Decionis vs Lakera
AI security for protecting generative AI applicationsChoose Decionis when
Choose Decionis when you need deterministic governance at the business decision layer.
Choose Lakera when
Choose Lakera when the main concern is securing GenAI applications against model-layer threats and unsafe inputs.
| Comparison area | Decionis | Lakera |
|---|---|---|
| Primary job | Govern execution decisions before they happen | Secure GenAI applications and AI attack surfaces |
| Best fit for | CFO, COO, risk, procurement, and operations teams | Security and AI platform teams |
| Core artifact | Decision Dossier with policy and accountability | AI security controls and protection posture |
| Tradeoff | Not an AI application security platform | Not a deterministic business execution control plane |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Not the primary focus. Lakera protects AI applications and attack surfaces rather than gating downstream business execution. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Security posture and detection outputs rather than Decision Dossiers and validation packs for certified actions. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Security-oriented detections, not one confidence-scored governed business verdict before execution. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Can block unsafe AI interactions, but deliberate do-nothing logic for enterprise execution control is not the central job. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Not positioned as a before-money-moves execution control plane. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can sit in AI stacks, including Google Cloud, but as AI security rather than the cloud-agnostic execution control plane with preserved approvals. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Security controls and detection posture rather than explicit org-wide and per-decision execution kill switches. |
How is Decionis different from Lakera?
Lakera addresses AI security concerns around GenAI applications. Decionis addresses whether a business action should be allowed to execute under policy, with evidence and accountability attached before the downstream system commits the action.
Who is Decionis for here?
Decionis is for organizations that have high-stakes workflows where AI recommendations, approvals, or routing choices can create real financial or operational consequences.
What are the tradeoffs?
Decionis is not an AI threat detection or prompt-defense platform. If your top priority is securing AI applications themselves, Lakera is closer to that problem.
Why would a CFO choose Decionis?
A CFO chooses Decionis to stop uncontrolled execution, prove policy adherence, and reduce preventable downstream loss from bad approvals or bad automation.
Decionis vs LangChain Guardrails
Developer middleware for guardrails in AI applicationsLangChain Guardrails helps developers manage guardrails around AI workflows. Decionis gives your team an execution control plane that decides whether enterprise actions can proceed before money moves or systems change.
Read the full comparison →
Decionis vs LangChain Guardrails
Developer middleware for guardrails in AI applicationsChoose Decionis when
Choose Decionis when your team needs a proceed, hold, or escalate answer at the approval, spend, routing, or operational action layer.
Choose LangChain Guardrails when
Choose LangChain Guardrails when the primary need is developer middleware around model and agent behavior.
| Comparison area | Decionis | LangChain Guardrails |
|---|---|---|
| Primary job | Policy-gated execution control | Developer guardrails for AI workflows |
| Best fit for | Enterprise operators and the people who own the budget | Developers and agent platform teams |
| Core artifact | Decision Dossier and policy proof | Workflow guardrails and middleware controls |
| Tradeoff | Less general-purpose for arbitrary agent stacks | Not built as a CFO-grade execution control plane |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Not the primary role. LangChain Guardrails focuses on developer middleware around models and agent workflows. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Workflow guardrails and middleware controls rather than Decision Dossiers and regulator-facing validation packs. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Guardrails around workflow behavior, not one confidence-scored certified verdict at the business action layer. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Can constrain AI workflow behavior, but deliberate hold logic for enterprise execution is not the core posture. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Not designed around before-money-moves governance for finance, procurement, and operations. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Can be used in AI stacks, but not as the cloud-agnostic execution control plane preserving approval paths, Decision Dossiers, and audit evidence. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Developer middleware controls rather than org-wide and per-decision kill switches for high-stakes execution. |
How is Decionis different from LangChain Guardrails?
LangChain Guardrails is aimed at application builders adding guardrails to AI workflows. Decionis is aimed at enterprise teams that need an execution control plane and audit-grade justification once a decision reaches the business layer and is about to affect a real workflow, payment, approval, or state change.
Can teams use both?
Yes. A team can use LangChain Guardrails at the model and agent layer, then use Decionis to determine whether a financial or operational action is allowed to execute.
What are the tradeoffs?
Decionis is not a general-purpose developer middleware library. If your main job is building agent infrastructure, LangChain Guardrails is closer to that need.
Why would a CFO choose Decionis?
A CFO chooses Decionis because it creates deterministic control over execution, accountability, and audit evidence rather than only improving application-layer safety.
Decionis vs Cohere Health
AI-assisted prior authorization and clinical intelligence for health plans and providersCohere Health generates clinical-intelligence prior authorization recommendations. Decionis governs whether the resulting action is authorized to execute and produces a portable signed Decision Dossier. They sit at different layers and can run together.
Read the full comparison →
Decionis vs Cohere Health
AI-assisted prior authorization and clinical intelligence for health plans and providersChoose Decionis when
Choose Decionis when the requirement is execution authority and audit defensibility across referral, prior authorization, and procurement workflows — one verdict of proceed, hold, or escalate, with signed proof that travels to a regulator.
Choose Cohere Health when
Choose Cohere Health when the requirement is the clinical intelligence itself: evidence-based prior authorization recommendations and medical-necessity determinations inside utilization management.
| Comparison area | Decionis | Cohere Health |
|---|---|---|
| Primary job | Govern execution authority and produce audit proof before an action commits | Generate clinical prior authorization and medical-necessity recommendations |
| Layer | The authority and audit layer around the decision, across workflows | The clinical intelligence inside the prior authorization decision |
| Best fit for | Compliance, governance, revenue cycle, and operations leaders | Utilization management and clinical operations teams |
| Core artifact | Signed Decision Dossier with policy version and authority verification | Evidence-based clinical recommendation and UM decision |
| Relationship | Engine-agnostic — governs the action around any UM or PA system | Complementary clinical engine that Decionis can govern, not replace |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Focused on producing the clinical recommendation, not on gating whether the downstream action is authorized to execute across referral, procurement, and operational workflows. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Clinical decision records inside the UM workflow rather than a portable, cryptographically chained Decision Dossier plus org-level validation-pack model that travels to a regulator. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Clinical evidence and recommendations rather than one certified execution verdict — authorize, block, escalate, or restrain — at the action boundary. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Centered on medical-necessity determination rather than deliberate hold or restraint of an action pending verified human authority. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Strong inside clinical prior authorization, but not positioned as a before-the-action execution control plane spanning procurement and operations. |
| Google Cloud and Vertex AI stack fit with governance preserved | Cloud-agnostic. Decionis can expose a Vertex AI Extension or ADK tool surface while keeping the execution-time decision authority, Decision Dossiers, and audit evidence inside Decionis Protocol. | Clinical AI delivery rather than a cloud-agnostic execution control plane that preserves approval paths and Decision Dossiers across stacks. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Clinical workflow controls rather than explicit org-wide and per-decision execution kill switches as a public proof point. |
How is Decionis different from Cohere Health?
Cohere Health operates inside the clinical decision: it produces evidence-based prior authorization and medical-necessity recommendations. Decionis operates one layer over: it does not diagnose or determine medical necessity. It governs whether the action that follows a recommendation is authorized to execute under institutional policy, verifies the right approval authority, and signs the reasoning into a portable Decision Dossier for audit.
Can Decionis and Cohere Health run together?
Yes. Cohere Health can generate the prior authorization recommendation while Decionis governs the execution boundary around it — confirming the licensed-clinician gate where the law requires one, routing escalations, and producing the signed audit dossier. Decionis is engine-agnostic: it can sit around any utilization-management or prior-authorization system rather than replacing it.
Who is Decionis for in this comparison?
Decionis is for the compliance, governance, and operations owners who must prove who approved an action and on what basis — across referral, prior authorization, and procurement workflows — not only for the clinical team producing the recommendation. It is deployed shadow-mode-first so governance value is observed before any enforcement.
What are the tradeoffs?
Decionis is not a clinical-intelligence or medical-necessity engine and does not author coverage criteria. If the need is the clinical recommendation, a utilization-management product such as Cohere Health is the fit. If the need is execution authority, escalation routing, and a portable, tamper-evident audit trail across workflows, Decionis is the control plane.
Decionis vs native Shopify discount controls
Built-in Shopify Plus discount combinations, Scripts/Functions, and Flow as a do-it-yourself guardrailShopify's native discount combinations, Scripts, and Flow can express rules, but they don't verify margin against a real cost basis, don't fail closed on a wrong cost, and leave no signed, portable proof of what was held and why. Decionis is the deterministic margin-governance layer that does — and it installs read-only first.
Read the full comparison →
Decionis vs native Shopify discount controls
Built-in Shopify Plus discount combinations, Scripts/Functions, and Flow as a do-it-yourself guardrailChoose Decionis when
Choose Decionis when the requirement is a deterministic margin floor enforced at checkout against a verified cost basis, a read-only Shadow Mode that shows the dollars at risk from your existing automation before you enforce, and a signed Decision Dossier per held order for finance and dispute defense.
Choose native Shopify discount controls when
Native Shopify controls are the right starting point for simple, static discount limits and combination rules that don't need a verified cost basis, cross-channel state checks, or an auditable signed record of every held decision.
| Comparison area | Decionis | native Shopify discount controls |
|---|---|---|
| Primary job | Enforce a deterministic net-margin floor at checkout against a verified cost basis | Express static discount combinations, caps, and rule-based automations |
| Cost-basis awareness | Evaluates real unit cost (ERP/Shopify) and fails closed when cost is unknown | No cost-basis concept — a percentage cap can still ship below cost |
| Before-enforcement evidence | Read-only Shadow Mode + Drift Report quantifies exposure from your own data first | No equivalent — rules are either off or live |
| Core artifact | Signed Decision Dossier per held order, sealed into a tamper-evident ledger | Order tags / logs, not a signed, portable proof of the held decision |
| Relationship | Sits beside native rules and your pricing engine — governs the margin floor around them | The platform baseline Decionis layers deterministic governance on top of |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Native rules fire inside Shopify but don't gate on a verified net-margin/cost-basis check before the discount commits, and don't fail closed when cost is unknown. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Order tags, logs, and Flow run history rather than a portable, cryptographically chained Decision Dossier and Decision Ledger that finance can export and verify. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | A rule either applies or doesn't, with no single certified verdict (allow / hold / review) carrying the margin math and policy version that produced it. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | No deliberate review/hold when the cost basis is missing — the rule simply proceeds on whatever data is present rather than restraining the action. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Operates at the discount-rule layer, not as a before-the-sale margin control plane that verifies cost-basis truth at admission and margin at execution. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Toggling rules individually in admin, without a governed org-wide and per-rule monitor→enforce kill switch backed by an audit record. |
Can't I just use Shopify's native discount combinations and limits?
For simple static caps, yes. But native combination rules don't know your cost basis, so they can't enforce a true net-margin floor — a 40%-off rule still ships a loss on a low-margin SKU. They also don't verify that the cost a pricing app pulled matches your ERP, don't fail closed when cost is unknown, and don't leave a signed, portable receipt of what was held and why. Decionis adds the margin math, the cost-basis truth check (Gate 1), and the signed Decision Dossier.
Doesn't a custom Shopify Function or Script already do this?
A custom Function can express a threshold, but you then own the cost-basis sourcing, the fail-closed behavior, the audit trail, the cross-channel inventory truth, and the read-only rollout — and you maintain it. Decionis ships those as a governed product: a deterministic Function plus admission gate, real unit-cost evaluation, a tamper-evident Decision Ledger, and a one-click monitor→enforce toggle with a kill switch.
How does Decionis prove value before I trust it to block checkouts?
It installs in read-only Shadow Mode and evaluates your real orders, discounts, and price changes — or your last 14 days on demand — recording what it would have caught into a Drift Report. The dollars at risk are computed from your real cost data (with a clearly-labeled estimate where cost is missing, never a fabricated number). Native rules give you no equivalent before-enforcement evidence.
What are the tradeoffs?
Decionis is a margin and pricing-integrity control plane, not a merchandising or repricing engine and not a fraud tool — it governs the floor around your pricing decisions, it doesn't make them. If your needs are met by static native discount caps with no cost-basis verification or audit requirement, native Shopify controls are simpler. If you run dynamic/AI pricing where a drift can leak real money, Decionis is the deterministic guard.
Decionis vs Agentis
A margin-governance layer (hycos.ai) that markets real-time, COGS-aware margin-floor enforcement blocking orders at checkout, MAP enforcement, and a per-evaluation audit trailAgentis positions itself as an AI-powered margin governance layer with COGS-aware margin-floor enforcement at checkout. Decionis is one deterministic gate that governs coupon-stacking, margin, over-selling, and rogue-agent actions together in under 120ms, and seals a signed, non-repudiable Ed25519 Decision Dossier per decision — not a plain audit log. It installs read-only first, with no demo required.
Read the full comparison →
Decionis vs Agentis
A margin-governance layer (hycos.ai) that markets real-time, COGS-aware margin-floor enforcement blocking orders at checkout, MAP enforcement, and a per-evaluation audit trailChoose Decionis when
Choose Decionis when you need one deterministic gate across coupon-stacking, margin, multi-channel over-selling, and rogue-agent actions — not margin alone — enforced in a hard sub-120ms budget, and a signed, reproducible Ed25519 Decision Dossier per decision that finance and disputes can independently verify. You can start today in self-serve read-only Shadow Mode without booking a demo.
Choose Agentis when
Agentis may be the right fit if your requirement is narrowly a COGS-aware margin floor and MAP enforcement, and its markets that as an AI-powered layer. If margin enforcement in isolation is all you need and a per-evaluation audit log is sufficient, Agentis positions itself for that scope.
| Comparison area | Decionis | Agentis |
|---|---|---|
| Scope of the gate | One deterministic gate across coupon-stacking, net-margin floor, multi-channel over-selling, and rogue-agent actions in a single pass | Agentis positions itself around COGS-aware margin-floor enforcement and MAP — margin-centric rather than one gate across all four |
| Core artifact | Signed, non-repudiable, reproducible Ed25519 Decision Dossier per decision, sealed into a tamper-evident ledger | Agentis markets a per-evaluation audit trail — a log rather than an independently verifiable signed proof |
| Latency | Hard sub-120ms deterministic decision budget at checkout | Agentis markets real-time enforcement without a published hard latency guarantee |
| Decision model | Deterministic — the same inputs and policy version always produce the same verdict, which is what makes the dossier reproducible | Agentis positions itself as an AI-powered margin governance layer |
| Evaluation path | Self-serve read-only Shadow Mode first — no demo, no checkout changes, reversible per rule | Agentis is marketed through a vendor-led enforcement rollout rather than a documented self-serve read-only install |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Agentis markets margin-floor enforcement at checkout, but positions itself around the margin dimension rather than one gate that also holds coupon-stacking, over-selling, and rogue-agent actions before the order commits. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Agentis markets a per-evaluation audit trail rather than a portable, cryptographically signed Ed25519 Decision Dossier and Decision Ledger that a third party can independently verify. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Agentis positions itself around margin allow/block rather than a single certified verdict (authorize / block / escalate / restrain) carrying the margin math and policy version across every governed dimension. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Agentis positions itself around enforcing a margin floor rather than a deliberate hold/restrain when cost basis or policy inputs are missing across coupon, over-sell, and agent-action checks. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Agentis markets checkout-time margin enforcement rather than a single before-the-sale control plane that verifies cost-basis truth and governs coupon, over-sell, and rogue-agent actions together. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Agentis markets margin enforcement toggles rather than a governed org-wide and per-decision monitor→enforce kill switch backed by an audit record. |
Isn't Agentis already a margin governance layer that blocks orders at checkout?
Agentis positions itself that way — it markets real-time, COGS-aware margin-floor enforcement that blocks orders at checkout plus MAP enforcement. Decionis governs more than margin: one deterministic gate evaluates coupon-stacking, the net-margin floor, multi-channel over-selling, and rogue-agent actions in a single pass, so you don't stitch together separate tools or accept that only the margin dimension is guarded.
Agentis says it keeps an audit trail per evaluation. How is a Decision Dossier different?
An audit trail records that a decision happened. A Decionis Decision Dossier is a signed, non-repudiable artifact — cryptographically sealed with an Ed25519 signature and reproducible — so a third party (finance, a card network, a dispute reviewer) can independently verify the exact policy version, inputs, and margin math that produced the verdict. Agentis markets a per-evaluation audit trail; Decionis produces portable, verifiable proof rather than a log entry you have to trust.
Is Decionis AI-powered like Agentis?
No, and that is deliberate. Agentis markets itself as AI-powered. Decionis is deterministic: the same order, cost basis, and policy version always produce the same verdict, and every decision returns in a hard sub-120ms budget. Determinism is what makes the Decision Dossier reproducible and what lets finance and disputes rely on it — a probabilistic model can't offer the same non-repudiable guarantee.
How do I evaluate Decionis versus Agentis without a sales cycle?
Decionis installs in self-serve, read-only Shadow Mode first — no demo, no checkout changes. It evaluates your real orders, discounts, and price changes and records what it would have caught, so you see the dollars at risk before you enforce anything, and every rule is reversible per rule. You can compare the actual before-enforcement evidence rather than a scripted walkthrough.
What are the tradeoffs?
Decionis is a deterministic execution control plane, not an AI repricing or merchandising engine — it governs the gate around your pricing and fulfillment decisions, it doesn't make them. If your need is narrowly a margin floor and MAP enforcement and a per-evaluation log is enough, Agentis positions itself for that. If you need one gate across coupon-stacking, margin, over-selling, and rogue-agent actions with signed, reproducible proof, Decionis is the deterministic guard.
Decionis vs Runta
A microVM/sandbox execution layer for AI agents (a16z-backed) that governs where an agent runs — process isolation, controlled network egress, credential proxying so raw keys stay out of the runtime, and replayable execution recordsRunta and Decionis both say “execution layer,” but they govern different altitudes. Runta governs where an agent runs — the sandbox: microVM isolation, egress allow-listing, credential injection, and replayable execution records. Decionis governs whether a specific business action is allowed at the moment of execution — it intercepts and consumes the action inline (ISO-8583 payment authorization, native bot actions, workflow pre-commit) and seals a signed, reproducible Ed25519 Decision Dossier. They are complementary layers, not substitutes.
Read the full comparison →
Decionis vs Runta
A microVM/sandbox execution layer for AI agents (a16z-backed) that governs where an agent runs — process isolation, controlled network egress, credential proxying so raw keys stay out of the runtime, and replayable execution recordsChoose Decionis when
Choose Decionis when you need a policy verdict on the business meaning of an action — this refund, this payout, this order’s margin, this payment-authorization message — returned before the action commits, plus portable signed proof a third party can verify offline. Decionis intercepts and consumes the execution inline at the semantic boundary and returns authorize / block / escalate / restrain with the policy version and business math attached.
Choose Runta when
Choose Runta when the job is to contain the agent’s compute environment: isolate the process, allow-list network egress, keep raw credentials out of the runtime, and replay what the process did. Runta governs the runtime by construction; it is deliberately blind to business meaning. The two compose — an agent inside a Runta sandbox can call Decionis for the verdict and a single-use execution grant.
| Comparison area | Decionis | Runta |
|---|---|---|
| What it governs | The business decision/action at the point of execution — authorize / block / escalate / restrain on this refund, payout, order margin, or payment-authorization message | The compute environment the agent runs in — process isolation, network egress, credentials, CPU (the sandbox) |
| Semantic awareness | Understands the action’s economic/business content — margin, refund amount, payroll variance, duplicate invoice — and evaluates it against a versioned policy bundle | Blind to business meaning by design — governs approved endpoints and spend ceilings, not policy on the action itself |
| Interception point | Intercepts and consumes the action inline at the semantic boundary — ISO-8583 payment authorization, native bot actions, workflow pre-commit | Intercepts at the process/syscall/network boundary — the microVM sandbox around the agent |
| Core artifact / proof | Signed, reproducible Ed25519 Decision Dossier, offline-verifiable by a third party against a public JWKS | Replayable execution records — a process trace rather than an independently verifiable signed verdict |
| Relationship | Complementary — an agent inside a Runta sandbox can call Decionis for the verdict and a single-use, action-bound execution grant | A runtime-isolation substrate that composes beneath a decision-authority layer, not a replacement for one |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Runta enforces egress allow-lists and spend caps on the agent’s process, but does not return a policy verdict on whether a specific business action is allowed before the workflow, transaction, or state change continues. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Runta markets replayable execution records (process replay) rather than a portable, cryptographically signed Ed25519 Decision Dossier a third party can independently verify offline. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Runta governs process, network, and credential access rather than returning a single certified verdict (authorize / block / escalate / restrain) carrying the policy version and business math for the action. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Runta contains the runtime by construction (isolation, egress control) rather than deliberately holding or restraining a specific business action when policy inputs like cost basis, entitlement, or variance are missing. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Runta caps spend and restricts endpoints at the process boundary rather than evaluating the business action itself — this refund, this payout, this payment-authorization message — before money moves. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Runta offers process-level isolation and egress control rather than a governed org-wide and per-decision monitor→enforce kill switch over business actions, backed by a signed audit record. |
Isn’t Runta already the execution layer for AI agents?
Runta governs the compute environment — the process, network egress, and credentials the agent runs with. It knows whether a network call goes to an approved endpoint; it does not know whether “refund $4,000” or “run payroll” is allowed under your policy. Decionis governs the decision at the semantic execution boundary: it intercepts and consumes the action inline — an ISO-8583 payment-authorization message, a native bot action, a workflow pre-commit hook — and returns a policy verdict before the action continues. Different layers of the same stack; they compose rather than compete.
Runta caps agent spend and records what agents do. How is Decionis different?
A spend cap is a dollar ceiling on a process. A Decionis verdict evaluates the specific business action against your org’s policy bundle — coupon-stacking, the net-margin floor, a duplicate invoice, payroll variance — and returns authorize / block / escalate / restrain in a hard sub-120ms budget. And Runta’s execution records are process replay; a Decision Dossier is a signed, reproducible Ed25519 artifact a third party (finance, a card network, a dispute reviewer) can verify offline against a public JWKS. One is a trace you have to trust; the other is portable proof.
Does Decionis sandbox or isolate the agent like Runta does?
No — that is deliberately Runta’s job. Decionis is not a hypervisor, sandbox, or egress firewall. It sits at the action boundary and issues a single-use, action-bound execution grant that the downstream system requires before the action commits, so an allow cannot be replayed. Containment of the runtime and authorization of the action are different controls; a mature deployment uses both.
Can Decionis and Runta work together?
Yes, and that is the intended shape. An agent running inside a Runta microVM, about to take a consequential action, calls Decionis for the policy verdict and a signed execution grant. Runta contains where the agent runs; Decionis authorizes what it is allowed to do and proves the verdict. Runtime isolation sits beneath a decision-authority layer.
What are the tradeoffs?
Decionis will not isolate a process, restrict network egress, or keep raw credentials out of a runtime — pair it with a runtime-isolation layer for that. What Decionis does that a sandbox structurally cannot is understand the business content of an action and produce a signed, reproducible verdict at the point of execution. If you need process containment, that is Runta’s scope; if you need to govern and prove the business decision, that is Decionis.
Decionis vs Signifyd
Order-fraud & chargeback protectionSignifyd positions itself around order-fraud screening and chargeback-liability protection using a probabilistic identity and risk score. Decionis is a different job: it stops good-faith margin leakage — coupon-stacking, price drift, rogue-agent pricing, and over-selling — deterministically at checkout and seals a signed Decision Dossier. They are complementary.
Read the full comparison →
Decionis vs Signifyd
Order-fraud & chargeback protectionChoose Decionis when
Choose Decionis when the money you are losing is margin, not fraud: coupon-stacking, price drift, rogue-agent pricing, and multi-channel over-selling that ship on legitimate orders. Decionis enforces a deterministic net-margin floor at checkout in under 120ms and returns a signed, reproducible Decision Dossier per held order.
Choose Signifyd (order-fraud & chargeback protection; also Riskified, Forter) when
Choose Signifyd (or Riskified, Forter) when the problem is bad actors: card-not-present fraud, account takeover, and chargeback liability. These tools are designed to score identity and transaction risk and typically shift chargeback liability off the merchant — a job Decionis does not do.
| Comparison area | Decionis | Signifyd (order-fraud & chargeback protection; also Riskified, Forter) |
|---|---|---|
| Primary job | Prevent good-faith margin leakage (coupon-stacking, price drift, rogue-agent pricing, over-selling) at checkout | Screen orders for fraud and protect against chargeback liability |
| Decision model | Deterministic — verified cost basis and policy version produce the same verdict every time | Positions around a probabilistic identity and transaction risk score |
| Risk addressed | Legitimate orders that ship below your net-margin floor | Fraudulent orders, account takeover, and chargebacks |
| Core artifact | Signed, reproducible Decision Dossier per held order, sealed into a tamper-evident ledger | Fraud decision plus, typically, a chargeback guarantee on approved orders |
| Relationship | Complementary — governs the margin dimension a fraud tool is not designed to cover | Complementary fraud layer that can run alongside Decionis, not replace it |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Fraud platforms are designed to approve or decline on identity and transaction risk, not to gate on a verified net-margin/cost-basis check before a legitimate discount commits. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Typically a fraud decision and chargeback-guarantee record rather than a portable, cryptographically signed Decision Dossier and Decision Ledger that finance can independently verify. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | A probabilistic fraud score of approve/decline rather than one deterministic certified verdict carrying the margin math and policy version that produced it. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Designed to decline suspected fraud, not to deliberately hold a legitimate order when the cost basis is missing or a discount would breach the margin floor. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Positioned as fraud and chargeback protection at checkout rather than a before-the-sale margin control plane spanning coupon, over-sell, and rogue-agent actions. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | Fraud-model controls rather than a governed org-wide and per-decision monitor→enforce kill switch backed by an audit record. |
How is Decionis different from Signifyd?
They solve different problems that get conflated as 'we're losing money on orders.' Signifyd is designed to stop fraudulent orders and shift chargeback liability using a probabilistic identity and risk score. Decionis stops good-faith margin leakage on legitimate orders — coupon-stacking, price drift, rogue-agent pricing, and over-selling — deterministically, and signs a Decision Dossier for each held order. Fraud is about who is placing the order; margin governance is about whether a legitimate order ships below your floor.
We already run Signifyd. Do we still need Decionis?
Often yes, because a passing fraud check does not mean the order protects margin. A genuine customer stacking three valid coupons, or an AI pricing tool that drifted below cost, produces a clean, non-fraudulent order that Signifyd is not designed to hold. Decionis governs that margin dimension and leaves signed proof, so the two can run side by side — fraud screening on identity, Decionis on margin, coupon, over-sell, and rogue-agent risk.
Is Decionis probabilistic like a fraud score?
No. Fraud platforms are typically probabilistic by design — they estimate the likelihood a transaction is fraudulent. Decionis is deterministic: the same order, verified cost basis, and policy version always produce the same verdict, which is what makes the Decision Dossier reproducible and independently verifiable by finance or a dispute reviewer.
What are the tradeoffs?
Decionis is not a fraud, chargeback-guarantee, or identity-risk platform and does not assume chargeback liability. If the core need is stopping fraudulent orders and transferring chargeback risk, a fraud tool such as Signifyd, Riskified, or Forter is the fit. If the core need is preventing margin loss on legitimate orders with signed, auditable proof, Decionis is the deterministic guard.
Decionis vs manual margin reports
After-the-fact margin analyticsA margin report in BigQuery, a spreadsheet, or a BI dashboard detects margin loss days or weeks later — after the money is gone. Decionis prevents it by blocking the below-floor order inline at checkout in under 120ms and sealing signed proof. Detection versus prevention; retrospective BI versus an execution-time control plane.
Read the full comparison →
Decionis vs manual margin reports
After-the-fact margin analyticsChoose Decionis when
Choose Decionis when you need to stop margin loss before it ships, not read about it afterward. Decionis enforces a deterministic net-margin floor at the moment of checkout against a verified cost basis and returns a signed Decision Dossier per held order, so the leak is prevented and proven rather than discovered later.
Choose Manual margin reports (BigQuery, spreadsheets, BI dashboards) when
A margin report is the right tool when the goal is analysis and reporting — understanding trends, slicing margin by SKU or channel, and briefing finance. Reports are designed to explain what already happened; they are typically not an inline control that can hold an order at checkout.
| Comparison area | Decionis | Manual margin reports (BigQuery, spreadsheets, BI dashboards) |
|---|---|---|
| Primary job | Prevent below-floor orders inline at checkout against a verified cost basis | Detect and explain margin loss after orders have shipped |
| Timing | At execution time, in under 120ms, before the order commits | Retrospective — typically days or weeks after the fact |
| Detection vs prevention | Prevention — the leak is blocked before it ships | Detection — the leak is measured after the money is gone |
| Core artifact | Signed, reproducible Decision Dossier per held order, sealed into a tamper-evident ledger | A report, query result, or dashboard tile you reconcile and trust |
| Human dependency | Deterministic control that does not rely on someone watching a dashboard | Typically requires a human to notice, interpret, and chase the finding |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | A report reads data after the fact; it is not designed to gate a checkout on a verified net-margin/cost-basis check before the order commits. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | A query output or dashboard export you have to reconcile, rather than a portable, cryptographically signed Decision Dossier and Decision Ledger produced at the moment of the decision. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | Aggregated metrics and trends rather than one deterministic certified verdict (allow / hold / review) at the action boundary. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Reporting cannot hold an order; it records what already shipped rather than restraining a below-floor action when cost basis or policy is insufficient. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Retrospective analytics rather than a before-the-sale margin control plane that verifies cost-basis truth at admission and margin at execution. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | No enforcement surface to toggle — a report cannot switch between monitor and enforce, unlike a governed org-wide and per-decision kill switch with an audit record. |
We already pull a margin report. Isn't that enough?
A report tells you margin leaked after it already shipped — usually days or weeks later, once the order, discount, or price change is final and the money is gone. Decionis moves the same margin math to the moment of checkout and blocks the below-floor order inline in under 120ms, then signs a Decision Dossier as proof. Reporting is detection; Decionis is prevention. Most teams keep the report for analysis and add Decionis for the inline control.
Can't we just alert on the dashboard faster?
Faster alerts still fire after the order commits, so the loss is already booked by the time anyone reads them — and they typically require a human to notice, interpret, and chase it. Decionis evaluates each order deterministically at execution time and either allows, holds, or flags it before it ships, so prevention does not depend on someone watching a dashboard.
How is the proof different from a BI export?
A BI export is a retrospective calculation you have to trust and reconcile. A Decionis Decision Dossier is a signed, reproducible artifact sealed at the moment of the decision — it records the exact inputs, cost basis, policy version, and margin math that produced the verdict, so finance or a dispute reviewer can independently verify what was held and why rather than re-deriving it from a spreadsheet.
What are the tradeoffs?
Decionis is an execution-time control plane, not a BI or analytics suite — it is not designed to replace your warehouse, ad-hoc SQL, or dashboards for exploration and reporting. If the need is retrospective analysis and slicing, a margin report is the right tool. If the need is preventing below-floor orders inline with signed proof, Decionis is the deterministic guard that runs before the report ever records the loss.
Decionis vs custom Shopify Scripts / Functions
DIY checkout validationShopify Functions and the Validation APIs can reject an order at checkout, but you build and maintain the margin math yourself — without a verified cost basis, a signed non-repudiable Decision Dossier, or cross-channel/ERP coverage — and they are Shopify-only and easy to leave fail-open. Decionis is the governed, signed, cross-surface guardrail; a custom Function is unsigned bespoke code.
Read the full comparison →
Decionis vs custom Shopify Scripts / Functions
DIY checkout validationChoose Decionis when
Choose Decionis when you want a governed product rather than code you maintain: a deterministic checkout gate backed by a verified cost basis, fail-closed behavior when cost is unknown, a signed reproducible Decision Dossier per held order, cross-channel and ERP coverage, and a one-click monitor→enforce toggle with a kill switch.
Choose Custom Shopify Scripts / Functions (build-it-yourself) when
A custom Shopify Function is a reasonable starting point when the rule is simple and static, the team is happy to own and maintain it, and the requirement is Shopify-only with no need for a verified cost basis, cross-channel state, or a signed audit record. Functions are designed to reject an order at checkout, and for a basic threshold that can be enough.
| Comparison area | Decionis | Custom Shopify Scripts / Functions (build-it-yourself) |
|---|---|---|
| Build vs buy | A governed, maintained product — the deterministic gate, cost basis, and signed proof ship with it | Build-it-yourself bespoke code you own, extend, and maintain |
| Cost-basis awareness | Evaluates a verified unit cost (ERP/Shopify) and fails closed when cost is unknown | You source the cost yourself; a Function typically fails open when cost is missing |
| Core artifact | Signed, non-repudiable, reproducible Decision Dossier per held order, sealed into a ledger | Unsigned bespoke code with logs — no independently verifiable signed record |
| Coverage | Cross-channel and ERP-aware, governing the margin floor beyond a single storefront | Shopify-only by design |
| Rollout & control | Read-only Shadow Mode first, one-click monitor→enforce toggle, and a kill switch with an audit record | You build the read-only path, the toggle, and the audit trail — or go straight to live |
| Policy-gated execution before money moves or system state changes | Yes. Your team gets the policy answer before a workflow, approval, transaction, or system state change continues. | Functions can reject an order at checkout, but the verified net-margin/cost-basis check and fail-closed behavior are yours to build; left as bespoke code they are easy to leave fail-open. |
| Decision Dossier and audit trail | Yes. Every certified execution can return a portable signed Decision Dossier plus broader org-level validation packs. | Application logs from custom code rather than a portable, cryptographically signed Decision Dossier and Decision Ledger that finance can export and independently verify. |
| Confidence-scored single verdicts | Yes. Decionis returns one certified verdict such as authorize, block, escalate, or restrain rather than leaving multiple interpretations at the point of action. | A hand-written rule either applies or does not, with no single certified verdict carrying the margin math and policy version that produced it unless you build that yourself. |
| Do-nothing / restraint logic | Yes. Decionis can deliberately hold or restrain action when confidence, evidence, or policy is insufficient. | Deliberate hold-when-cost-is-unknown is not built in; a Function typically proceeds on whatever data is present rather than restraining the action. |
| Execution-before-money-moves governance | Built as the execution control plane before spend, approvals, routing, or high-stakes operations proceed. | Operates at the single-storefront validation layer rather than as a cross-surface before-the-sale margin control plane verifying cost-basis truth at admission. |
| Org-wide and per-decision kill switches | Available. Decionis keeps both org-wide and per-decision kill switches with audit logging. | You would build your own enable/disable path in code, rather than a governed org-wide and per-rule monitor→enforce kill switch backed by an audit record. |
Can't a custom Shopify Function already reject the order at checkout?
Yes — Functions and the Validation APIs can reject an order at checkout. The gap is everything around the rule: with a Function you build and maintain the margin math yourself, you source and verify the cost basis yourself, and you decide what happens when cost is unknown — which is typically fail-open, so a missing cost silently ships a loss. Decionis ships that as a governed product: a deterministic gate with a verified cost basis, fail-closed behavior, and a signed Decision Dossier per held order.
What does Decionis give me that my own Function doesn't?
A verified cost basis (rather than whatever number your code happens to read), a signed, reproducible Decision Dossier that finance or a dispute reviewer can independently verify, cross-channel and ERP coverage instead of Shopify-only logic, and a governed monitor→enforce toggle with a kill switch and audit record. A custom Function is unsigned bespoke code with none of those guarantees unless you build and maintain them yourself.
Isn't building it ourselves cheaper?
The first version looks cheap; the ongoing cost is ownership. You maintain the cost-basis sourcing, the fail-closed behavior, the audit trail, the cross-channel inventory truth, and the read-only rollout as Shopify's APIs and your catalog evolve. Decionis is designed to provide those as a maintained product, so the margin math and its signed proof are not one more bespoke system your team has to keep alive.
What are the tradeoffs?
Decionis is a governed margin and pricing-integrity control plane, not a developer framework — if your requirement is genuinely a single static Shopify-only rule you are content to own, a custom Function is simpler. If you need a verified cost basis, fail-closed behavior, a signed non-repudiable Decision Dossier, and cross-surface coverage, Decionis is the build-vs-buy answer that avoids maintaining unsigned bespoke code.