AI inside controlled workflows

AI should remove repetition — not authority.

MALHUT's AI layer is designed to prepare, classify, check, summarize and prioritize work inside the same tenant, permission and approval boundaries as the rest of the platform. Model choice never expands system authority.

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Verified context

AI preparation

Policy check

Human decision

Authorized execution

Receipt & audit

Where AI can assist

Use AI where speed helps. Keep decisions where accountability matters.

Catalogue & localization

Prepare structured listing drafts and localization suggestions from approved source product data.

Readiness checks

Surface missing fields, inconsistent values and workflow blockers before work moves forward.

Operations triage

Prioritize catalogue, inventory, pricing and synchronization exceptions from verified operating signals.

Reporting

Prepare summaries of operating changes, exceptions and next actions for management review.

Advertising support

Prepare campaign observations and recommendations while spend and material changes remain approval-controlled.

Knowledge support

Draft internal responses and operating guidance from controlled context without bypassing source or permission boundaries.

Human authority

Sensitive actions do not become autonomous simply because AI is available.

The default MALHUT control model keeps material commercial, account and publication decisions behind explicit authority.

01Publish, materially change or retire a marketplace listing.
02Change target commercial price or other material selling terms.
03Launch, stop or materially change advertising spend.
04Change seller-account permissions, credentials or connection authority.
05Approve regulated, legal, safety or other sensitive product claims.
06Create a financial commitment or contractual obligation.

Automation architecture

Provider-neutral AI, structured outputs and an auditable execution path.

Task-specific model routing

The product boundary should choose a model by task and verified quality, not hard-code one AI brand into business logic.

Structured output

AI output enters typed workflow records instead of becoming an unreviewed free-text command.

Policy & approval gate

Permissions, tenant scope, action policy and required approval are checked independently of model output.

Execution adapter

Only an authorized connector or internal command boundary may perform an external action.

Failure & recovery

Operational automation uses bounded retry, explicit failure states and reviewed recovery rather than silent infinite loops.

Audit & observability

Proposal, decision, execution result and relevant provenance remain traceable without exposing secrets or raw provider payloads.

AI proposes. MALHUT controls. Manufacturer approves where required.

AI boundary

Controlled rollout, not blanket autonomy

AI capabilities are enabled module by module. This page describes the MALHUT product-control model; it does not mean every AI capability or marketplace connector is active in every account.

Build automation around your real operating process.

Start with the manufacturer, catalogue, target marketplaces and approval model. MALHUT can then define where software, AI assistance and human operations should sit in the workflow.

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