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About Axtor
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What is Axtor?
Axtor is a runtime control engine for Agentic AI. It evaluates proposed actions across scope, intent, evidence, policy, authority, and risk before execution, then returns a runtime outcome such as ALLOW, BLOCK, CLARIFY, or APPROVAL. See how Axtor works.
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Why isn't agent permission enough?
Technical permission establishes what an agent can access or execute. It does not establish whether a specific proposed action matches the intended request, relevant evidence, policy, authority, and risk context. Axtor evaluates that proposed action before enterprise execution controls enforce it.
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Is Axtor an authorization or IAM platform?
No. Axtor complements IAM, policy engines, approval systems, and other deterministic controls rather than replacing them. Axtor evaluates the proposed action at runtime, while existing enterprise controls remain responsible for deterministic permissions, approvals, and execution.
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Does Axtor replace human approval?
No. Axtor can identify when a proposed action is sufficiently supported, when clarification is needed, or when an APPROVAL outcome should route the action to a human or higher authority before execution.
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How it works
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What does Axtor evaluate before an action is allowed to proceed?
Axtor evaluates the proposed action across scope, intent, evidence, policy, authority, and risk. Relevant enterprise and external context can inform those dimensions. The resulting runtime outcome informs the workflow, while deterministic controls still enforce execution.
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Does Axtor search every conversation and historical record?
No. Axtor is designed to retrieve or receive the relevant evidence chain connected to the proposed action and workflow rather than blindly searching all historical enterprise data.
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How does Axtor handle unclear or conflicting intent?
Axtor treats uncertainty and disagreement as signals. When the evidence does not support a clear conclusion, the runtime outcome can be CLARIFY or APPROVAL rather than guessing. The action can be reassessed after clarification or approval.
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Can Axtor work with existing AI agents and enterprise systems?
Yes. Axtor is designed to sit in the runtime path between an agent's proposed action and enterprise execution controls. It can integrate with relevant CRM, contact center, payment, identity, ERP, or internal API systems. Explore Axtor solutions.
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Use cases
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What kinds of actions are considered consequential?
Examples include refunds, credits, payments, account or access changes, disclosure of data, approvals, cross-border actions, procurement decisions, and operational changes with meaningful business or customer impact.
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Which industries can use Axtor?
Potential settings include Financial Services, Commerce & Payments, Healthcare administrative workflows, Logistics & Supply Chain, Travel & Hospitality, Food & Beverage, and Enterprise Operations.
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Can Axtor handle cross-border actions?
Axtor can evaluate relevant cross-border context supplied by the workflow. Geography may affect policy, authority, jurisdiction, or risk, but location alone should not determine the runtime decision.
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Security, privacy, and compliance
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Does Axtor make legal or regulatory decisions?
No. Axtor can evaluate trusted evidence and constraints supplied by enterprise systems, policies, and other configured sources. It is not legal advice and does not replace legal or compliance judgment.
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Does Axtor require access to all enterprise data?
No. The intended architecture retrieves or receives only the evidence and context relevant to the proposed action and connected workflow through agreed integrations.
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How does Axtor handle privacy?
Axtor is designed around relevant, scoped evidence rather than unrestricted data access. Website information and current privacy practices are described in the Axtor Privacy Policy.
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Pilot
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What is an Axtor pilot?
A pilot starts with one clearly defined consequential action and evaluates how Axtor can apply runtime control to that workflow. It can compare ALLOW, BLOCK, CLARIFY, and APPROVAL outcomes against representative cases.
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What should we bring to a pilot discussion?
Bring the proposed action, why it is consequential, the systems involved, the evidence or control inputs available, the current stage of AI or automation, and the outcome you want to test.
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Do we need to already have AI agents in production?
No. A pilot can begin with a representative workflow, sample evidence, and shadow-mode evaluation before any live execution path is changed.
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How do we start?
Describe one consequential workflow on the Explore a Pilot page, or contact Axtor with an initial question.