72-hour delivery timeline
The 72-hour clock starts only after one workflow, scope, payment, and safe starting materials are confirmed. This page explains the delivery path without implying that this public site has a live checkout, automatic scheduler, or automatic customer record.
Use redacted examples only. The audit does not require passwords, private customer lists, live production access, or customer-facing messages before human review.
Before hour 0
The intake result is a scoping aid. A useful audit needs enough buyer-safe evidence to inspect one repeated workflow and enough agreement on what should stay human-approved.
Confirm the chosen workflow, useful redacted materials, business context, scope boundary, payment status, and what a person must approve before customers see anything.
Map triggers, inputs, owners, tools, status changes, waiting time, rework, customer-visible moments, and failure modes so the report reflects the actual handoff.
Rank AI assistance candidates by payback, evidence strength, confidence, complexity, customer or revenue risk, data sensitivity, and review clarity.
Turn the safest opportunity into a practical pilot ticket with prompts, SOP notes, owner responsibilities, review queue, tool-stack readiness, and what should remain manual.
Check for unsupported ROI claims, missing assumptions, unsafe automation suggestions, unclear review rules, sensitive-data requests, and gaps that should be labeled before delivery.
Deliver the Payback Map so the buyer can decide whether to pilot the first workflow, gather more evidence, defer implementation, or scope a separate build.
What arrives by delivery
The finished report is meant to make the next operating decision easier: which workflow to improve first, what the expected payback depends on, what AI can safely assist with, and where people still approve the work.
Current steps, owners, tools, handoffs, delays, rework loops, and customer-visible risk points.
Opportunity scores with assumptions, confidence, risk, complexity, and measurable next-step notes.
Where AI should draft, research, route, summarize, report, or wait for better inputs before helping.
Who frames tasks, reviews outputs, approves customer-facing work, escalates exceptions, and checks failures.
Reusable prompts, field notes, review checklist, and operating steps for the first safe test.
Metrics, weekly review habit, failure log, expansion rules, and questions to verify before implementation spend.
Delivery questions
The timeline is meant to reduce surprise. It does not change the current public-site gates around checkout, scheduling, live customer data, or implementation.
No. It helps decide whether there is enough signal. The audit starts only after scope, payment, and safe starting materials are confirmed.
The right next step may be gathering examples, clarifying owners, or choosing a narrower workflow before paying for the audit.
No. The report may recommend assisted drafting or routing, but customer-visible work stays human-reviewed unless a later implementation scope says otherwise.
Use the report to pilot one safe step, defer, gather missing evidence, or scope implementation separately after reviewing the risks and assumptions.