Draft and sources checked: 19 October 2026. Examples are hypothetical, not Altiport client results.
The example is illustrative and describes no Altiport client engagement.
Executive answer
Choose a specific customer outcome and map how it gets delivered today. Then design the future workflow, including evidence, decision rights, exceptions, and recovery. Technology selection becomes more concrete once you know which steps require generation, which require deterministic rules, and which remain human judgments.
The useful output is a workflow people can operate and measure. A persuasive demonstration is only one input to that design.
Start at the boundaries
Define the trigger and the completed outcome. “Handle customer email” is too broad. “Receive a standard replacement-part inquiry and deliver a reviewed quotation with verified availability” has a beginning, an end, and a customer expectation.
Gather representative examples, including incomplete requests, conflicting records, complaints, and rare exceptions. Walk through them with the people doing the work. Record systems, copies, approvals, queues, and decisions. Separate active handling time from elapsed time: a five-minute task waiting two days for approval requires a different intervention from a two-hour preparation task.
For each step, ask whether it should exist. Remove redundant approvals only with the process owner’s agreement. Standardize inconsistent inputs where practical. Use conventional rules where the answer is defined and repeatable. Reserve AI for a specific contribution, such as interpreting an unstructured request or preparing a grounded explanation.
Anthropic distinguishes predefined workflows from agents that dynamically direct their own processes, and recommends increasing complexity only when needed. That is a useful architecture distinction when deciding how much flexibility this workflow actually requires. Source: Anthropic
Worked example: replacement-part inquiry
Hypothetical illustration. A distributor currently receives an email, searches a product catalog, checks inventory, asks a specialist about ambiguous requests, prepares a quote, obtains approval, and sends it. A second employee later re-enters accepted details into the order system.
The team proposes this future state:
- Capture the request and assign a unique case identifier.
- Extract the requested part, quantity, and customer question; flag missing information.
- Retrieve current records from approved sources with their timestamps.
- Apply deterministic checks for required fields, permitted products, and valid record matches.
- Prepare a draft quote packet, with evidence attached to each relevant assertion.
- Route ambiguity or conflicting records to a specialist. A commercial owner approves price and delivery commitments.
- Send only the approved version and record its identifier.
- On acceptance, transfer approved fields to the order process; reconcile the result before marking the case complete.
This design changes the handoff and creates a clearer evidence trail. It may also make it practical to consider more small inquiries. Neither improvement is established until tested.
Suppose 100 weekly inquiries previously required 25 minutes each, or 2,500 minutes. In the hypothetical future, 70 standard cases require 12 human minutes and 30 exceptions require 30 minutes: 840 + 900 = 1,740 minutes. That releases 760 minutes, or 12 hours 40 minutes, weekly. The average becomes 17.4 minutes. Test these assumptions with corrections included; a slower exception path can consume much of the apparent gain.
Define what “human review” means
Assign a named role and a specific decision. “A person checks it” leaves unanswered what they must verify, what evidence they see, and whether they can reject or pause the work.
In this illustration, the commercial approver checks price and commitments against current approved records. The specialist resolves part ambiguity. The operations owner monitors backlog and can disable the automated preparation step. The technical owner investigates failed transfers. One person may hold several roles, but each responsibility needs an explicit owner.
Tool access is also a design boundary. OpenAI’s function-calling documentation requires application-side execution of requested functions. The surrounding application therefore needs to enforce permissions and business checks; a model’s request is not itself business authorization. Source: OpenAI
Human accountability does not require a person to approve every routine output forever. For a later, separately authorized scope, test which checks can reliably establish correctness before an action: exact record matching, approved price rules, freshness, and reconciliation may support bounded automatic completion. Keep exceptions, new commitments, and unresolved judgment with the appropriate owner. Measure errors that escape the checks and the workload sent to people before changing the approval design.
Reusable workflow worksheet
Copy this structure for both current and future states. Add an actual sample case to every disputed step.
| Step | Input and evidence | Decision owner | Output | Failure or exception |
|---|---|---|---|---|
| Intake | Original request | Service operator | Case ID and fields | Missing quantity |
| Preparation | Approved catalog and inventory | Workflow owner | Referenced draft packet | Conflicting records |
| Approval | Draft and source evidence | Commercial approver | Approved version | Unacceptable commitment |
| Execution | Approved fields | Order operations | Recorded transaction | Duplicate or failed write |
| Reconciliation | System receipt | Operations owner | Confirmed completion | Partial completion |
For each exception, specify detection, queue, owner, customer communication, resolution evidence, and restart point. Include an unavailable source, an incorrect match, a changed request, a rejected draft, a repeated request, and a system outage. Do not retry a consequential action blindly when its previous outcome is uncertain.
Handoff checklist and limits
Before choosing a tool, confirm:
- Every step has an owner, an input, and a completion condition.
- Required source access and permissions are understood.
- Review includes evidence and enough staff capacity.
- Exceptions have a real destination and recovery path.
- Success measures include quality, elapsed time, throughput, and rework.
- A fallback process exists, and someone can pause the new workflow.
This is a design template, not a verified integration specification or safety assessment. Actual system capabilities and domain obligations must be checked. Use the resulting workflow to request a demonstration against your cases, then connect measured results to the business case.
Explore the approach to transformation or continue through the resource library.