Policy before execution — for every requester
Axiru evaluates policy while an action is still governable. The Stripe API call only happens after authorization — whether the request came from a human rep, an AI agent, or an automated script.
Security
Policy enforcement that holds — whether a human or an AI made the request.
Axiru's governance architecture was designed for a world where the entity requesting a refund might be a rep under pressure, an automated workflow with a bug, or an AI agent that has been manipulated. The enforcement layer doesn't trust the requester — it evaluates the request against your policy, every time, identically.
Architecture
Simple architecture, legible boundaries
Every event flows through one decision plane before any money moves.
Stripe Events
Refund Requests
Policy Rules
Role Context
↓
AXIRU DECISION PLANE
Replay + Simulation
Policy Evaluation
Approval Routing
Execution Controls
↓
Approved / Blocked
Immutable Ledger
Audit Exports
Technical controls
The controls that matter for any team composition.
These controls were designed for human support teams. They are also exactly the right architecture for AI agent deployments — because the failure modes are structurally identical. Governance at the enforcement layer holds regardless of who or what initiates the request.
Append-only ledger — sealed at the moment of decision
Governed flows record decision, rationale, approval state, and execution outcome in a durable timeline. Written once. Never modified. The authoritative record for audit, legal review, and board reporting — for human and AI decisions alike.
Audit-ready evidence — attached to every decision
Evidence stays attached to the decision path so finance and audit do not need to reconstruct context from multiple systems. Especially critical when AI agent decisions need to be defensible in a legal or regulatory context.
Role-based approvals — requester cannot self-authorize
Approver workflows separate requester, reviewer, and operator responsibilities. No human rep and no AI agent can approve its own request above its assigned threshold. Policy determines the approver, not the requester's confidence.
Deterministic enforcement — not model-based
Axiru's policy engine uses compiled deterministic logic, not a language model. The enforcement layer that governs AI agents cannot itself be prompted, drifted, or hallucinated. Policy rules are explicit, versioned, and human-authored.
Tenant-aware handling
Workspace context, policy evaluation, and access boundaries are organized so customers can reason clearly about review scope and control ownership — across teams that may include both human agents and AI automation.
Compliance
Where we are on compliance certification.
SOC 2 Type II — in progress
Axiru is currently pursuing SOC 2 Type II certification. Design partners receive our security architecture review and a draft controls narrative before audit scope is finalized.
If your procurement process requires specific compliance evidence, contact us — we will provide what is available and be direct about what is not yet complete.
Contact us about compliance →Next step
The enforcement layer that was missing — for human teams and AI teams alike.
Start free in shadow mode. Connect Stripe read-only and replay your last 90 days through Axiru's policy engine before enabling any live enforcement.
Start in shadow mode first. Move to live enforcement later.