Harborline Services is a fictional 240-person business-services company operating in three cities. It supports about 320 client organizations and processes customer requests, supplier invoices, employee questions, recurring reports, and marketing campaigns through a mixture of email, spreadsheets, shared drives, and a service desk.

The company wants practical AI improvements, but its leadership has imposed one rule: no AI output may create a financial, contractual, employment, security, or customer commitment without an accountable human decision.

Company Snapshot

Area Current state Baseline problem
Customer operations Shared inbox plus service desk 18% of cases are rerouted; urgent cases are sometimes found late
Finance Email invoices and spreadsheet trackers 7% require clarification; duplicate checks are inconsistent
Internal knowledge Policies across shared drives Staff ask repeated questions and cite outdated files
Marketing Interview notes, CRM exports, and newsletters Research is scattered and claims are reviewed late
Governance Different tools owned by different teams Logging, retention, and review rules are inconsistent

Operating Roles

  • Maya Chen, COO: accountable for operating performance and pilot approval.
  • Jon Bell, Support Manager: owns queues, priorities, and service levels.
  • Priya Nair, Controller: owns invoice, close, and approval controls.
  • Elena Ruiz, Marketing Director: owns external claims and editorial approval.
  • Sam Okafor, IT Lead: owns integrations, access, logging, and incident containment.
  • Nora Patel, HR Manager: owns policy sources and employee escalations.

Synthetic Intake Records

ID Channel Message
H-001 Customer email “The amount on invoice 7842 does not match our contract. We will pause payment until someone explains it.”
H-002 Support form “I cannot sign in after changing phones. I have a client presentation in two hours.”
H-003 Vendor email “Please update our bank details to the attached account before Friday’s payment run.”
H-004 Employee chat “Can I carry unused leave into next year? The handbook and portal seem different.”
H-005 Customer email “Everything is broken again. Call me.” No account number or service is identified.
H-006 Internal request “Please send the latest onboarding checklist to the new Singapore team.”

Synthetic Invoice Records

ID Vendor Amount Purchase order Control issue
INV-101 Northwind Office $4,820 PO-5502 Clean example
INV-102 Delta Hosting $12,000 Missing Purchase-order exception
INV-103 Northwind Office $4,820 PO-5502 Possible duplicate of INV-101
INV-104 Brightline Events $26,450 PO-5529 Amount exceeds approval threshold
INV-105 Apex Advisory $8,700 PO-5540 Bank-detail change requested by email

Approved Knowledge Sources

Source Owner Audience Review status
Leave and Attendance Policy v4.2 HR Manager All staff Current
Travel and Expense Policy v3.1 Controller All staff Current
Client Support Escalation Standard v2.5 Support Manager Support team Current
Information Handling Standard v1.8 IT Lead All staff Current
Onboarding Checklist v5.0 HR Manager Managers and HR Current
Leave FAQ v2.0 Former HR analyst All staff Stale; conflicts with v4.2 policy

Customer Feedback Samples

  1. “The team is helpful, but I have to repeat the account history every time.”
  2. “Reports arrive on time, although the commentary often tells us what the chart already shows.”
  3. “Your onboarding was smooth. The security questionnaire took too long.”
  4. “We like the service, but pricing changes are hard to understand.”
  5. “Support is fast for normal requests and slow when several teams are involved.”

Governance Constraints

  • Public AI services may not receive bank details, employee records, credentials, or unredacted contracts without an approved enterprise arrangement.
  • High-risk outputs require source evidence and a named reviewer.
  • The IT Lead may pause an AI workflow during an incident.
  • Finance approvals and payment release remain in the accounting system.
  • Customer-facing text must be approved by the owning team until a pilot proves a lower-risk path.
  • Logs retain workflow IDs and decision evidence, but must avoid unnecessary sensitive content.

Baseline Metrics

Metric Baseline
First-pass support routing accuracy 82%
Median intake-to-queue time 24 minutes
Manual invoice touch time 11 minutes
Knowledge-search time per repeated question 8 minutes
Newsletter production cycle 2.5 working days
High-risk cases missing required review 6% in the last sample

Suggested Cross-Module Capstone

Design one governed AI program for Harborline that:

  1. improves support intake;
  2. retrieves approved policy knowledge;
  3. extracts invoice fields without approving payment;
  4. creates a human review queue;
  5. defines evaluation, monitoring, and incident response;
  6. reports business value against the baseline metrics.

The final capstone should contain a workflow map, output contracts, a fixed test set, a control matrix, a measurement plan, and a go/revise/stop recommendation.