€39.99 focused audit · Client workflow reviews · Human-led optimization
AIAI ExpertsBook AI support
Home / Case Studies / Workflow Audit & Optimization
AI workflow audit & optimization case studies · €39.99

Two client audits that turned “something is off” into a prioritized technical fix list.

These case studies are based on workflow audits delivered for clients with existing AI setups. They show how a focused review can inspect the current flow, reproduce the main issue, identify the highest-value corrections and leave a concrete action plan.

Case Study A · Lead automation audit

Audit of a form → AI → CRM workflow that worked but created messy records

A client already had a live automation. Leads reached the CRM, but categories were inconsistent, duplicate records appeared and it was unclear whether the source data, AI step or workflow mapping needed attention first.

Service€39.99 · up to 60 minutes
Starting stackForm + automation + AI + CRM
Audit goalFind root causes and prioritize fixes
OutputAudit notes + action plan

What the client brought

  • Current workflow screens or diagram.
  • Examples of problematic CRM records.
  • A successful run for comparison.
  • Run history or screenshots where available.

A→Z audit

  1. Confirm intended flowMapped the current trigger, AI transformation, routing, CRM write and notification so expected behavior was explicit.
  2. Inspect representative failuresCompared good and bad runs to determine whether the issue originated in source data, prompt output, field mapping or downstream logic.
  3. Review AI instruction and schemaChecked whether free-form model output was being used where constrained fields or explicit unknown values were required.
  4. Review workflow logicChecked required-field validation, duplicate handling, retry behavior, branch order and failed-run visibility.
  5. Test one high-priority correctionWhere technically practical, adjusted one prompt, schema or mapping rule and reran a representative input.
  6. Prioritize next actionsSeparated immediate fixes, medium-priority improvements and larger rebuild items.

Audit artifacts

Current-flow snapshot
Root-cause observations
Prompt/schema issues list
Workflow logic issues list
Priority-ranked fixes
Recommended retest scenarios

Audit complete when

  • The main failure pattern had an evidenced likely cause instead of a vague guess.
  • The client had a ranked list of corrections and next steps.
  • At least one useful retest path was defined.
  • Work requiring a larger implementation scope was separated clearly from the audit.
Case Study B · Chatbot workflow audit

Audit of a chatbot that handled normal questions but failed on context and escalation

A client's existing chatbot answered straightforward questions well but became unreliable on multi-part requests, repeated itself and sometimes failed to hand complex situations to a human.

Service€39.99 · up to 60 minutes
Starting stackChatbot + prompt + knowledge + handoff
Audit goalLocate context and escalation weaknesses
OutputFix list + test checklist

What the client brought

  • Current system instructions or screenshots.
  • Knowledge/FAQ structure overview.
  • Examples of conversations that went wrong.
  • The intended human-escalation behavior.

A→Z audit

  1. Define failure scenariosSelected high-value examples covering multi-part questions, missing context, policy uncertainty and human handoff.
  2. Inspect instruction hierarchyLooked for duplicate rules, weak priorities, contradictions and unclear fallback conditions.
  3. Inspect knowledge/context flowReviewed whether outdated, duplicated or overly broad content competed with the intended source.
  4. Review escalation logicConfirmed expected behavior when the chatbot lacked evidence, detected a complaint or needed user-specific information.
  5. Run targeted testsReproduced the selected cases and compared behavior around one focused instruction or knowledge change where feasible.
  6. Deliver action planRanked prompt cleanup, knowledge cleanup, escalation changes and regression tests by impact and effort.

Audit artifacts

Failure scenario list
Instruction conflict findings
Knowledge/context findings
Escalation review
Priority-ranked changes
Mini regression checklist

Audit complete when

  • The client understood which layer most likely caused each selected failure.
  • Immediate changes were separated from larger implementation work.
  • A small retest set existed for validating the next changes.
  • Known platform/model limitations were documented rather than presented as guaranteed fixes.
The €39.99 service is a focused audit and optimization session, not a promise to rebuild a complex system in one hour. Larger corrections can continue through multi-session implementation packages.
Fixed-price focused review

Already have an AI workflow and want to know what to fix first?

Book the AI Workflow Audit & Optimization Session for €39.99, up to 60 minutes.

View the €39.99 audit View pricing