Collect examples
Use real messages, documents, calls or jobs to map the workflow edge cases.
Use case · Real build pattern, generalised
Product advisor and recommendation engine
Use product data, embeddings and conversational logic to help customers choose the right kit or package faster.
Based on real build patterns from the implementation pattern library, generalised for public explanation. This is not a named client claim, not a guaranteed metric and not a regulated-advice workflow.
Kit suggestion, product advisor, Shopify and semantic-search project notesHuman approval built inProduction handover, not demo theatre
Problem pattern
The work this kind of system removes
Customers struggle to choose the right product or kit when the catalogue is technical, stock changes and advice depends on project context.
A good first version is narrow: it should prepare cleaner information, reduce handoff friction and make review easier. It should not pretend to replace the people responsible for the decision.
Design controls
Define what AI can draft, what it must never decide and where escalation happens.
Build the queue
Connect inputs, summaries, status labels, dashboards and human review points.
Measure operations
Track time saved, backlog movement, missed handovers and review quality.
Next step
Want to turn this pattern into a real project?
Send one workflow, data source or operational bottleneck. We will help decide whether it needs AI, a simpler automation, better reporting, or no-AI-yet process cleanup.