Synthetic controls demonstration

From document to a draft someone can approve.

A purchase request arrives as a document. Someone rekeys the fields and chases what is missing before a draft can move. Try a fixed-format synthetic request and check what happens when information is missing or conflicting.

Inspect the control path

This is not a live AI model, ERP connector or client case study. It uses synthetic documents, deterministic parsing and validation, a human approval step and a simulated handoff.

Inspect the mechanism

A useful draft has a visible stop.

Compare the source with the draft, then review the exceptions. These examples are synthetic; this page does not accept document uploads.

Synthetic data. Deterministic checks. Fixed text-format purchase requests, not PDFs or free-form quotes. Checks run in this page; nothing is sent to a business system.

Choose a synthetic scenario, then run its checks.

Inspect scripted control cases

These cases exercise corrections, rejected drafts, duplicate submissions and simulated failure recovery. Scripted decisions are not your approval or a real human sign-off. They run separately from the interactive review above.

Read the controls source Read the synthetic fixtures Inspect source provenance

The no-build option

Check the tools you already have first.

If your purchasing or accounting system already supports document capture, draft records and approval rules, test that path before commissioning software. Availability depends on your product, plan and configuration.

For a small volume, a shared intake folder, a draft template and a named reviewer may be enough. Check the required fields and keep a manual exception log.

A custom workflow is worth considering only when the remaining handoffs, exceptions or review burden justify it. A valid outcome of discovery is to configure an existing tool, simplify the process or not build.

From demonstration to a scoped service

Agree the boundary before a build.

This demonstration is a discussion aid, not an implementation package or an extraction accuracy guarantee. A real workflow needs its own evidence, permissions and acceptance criteria.

Your workflow owner: Provides approved, representative samples; defines required fields, exception rules and the person allowed to approve a draft. Your team keeps responsibility for the business decision.
Amulet’s scoped work: Map one input-to-draft path, test the native-tool alternative, define validation and approval boundaries, and propose a bounded implementation only where the evidence supports it.
Agree together: Document formats and volumes, source-system access, data handling, review workload, failure recovery and measurable acceptance tests. Confirm cost and scope before implementation.
Outside this proof: Live AI extraction, OCR accuracy, authenticated approver identity, ERP writes, production security, monitoring and support. No document upload or live-system access is offered here.

Where a deeper review is useful, the AI Business BEEP paid diagnostic creates the decision basis. Implementation remains a separate go or no-go commitment.

The next conversation

Bring the handoff that keeps coming back.

Describe where documents arrive, what gets rekeyed, who checks the draft and what happens when it is wrong. An approximate volume and the system names help. Keep the first enquiry non-confidential.

Discuss this workflow

A problem-fit request, not a purchase or a promise to build.