The same job, two ways
Every promotion, a paid-search team rebuilds hundreds of ads across a big product catalog: research last year, rewrite the copy on-brand, map it into a bulk spreadsheet, QA it, and push it live under time pressure. Done by hand it's slow and error-prone. This demo shows the governed alternative — where AI can help, but deterministic rules and a human decide what actually ships.
✗ The wrong way
✓ The governed way
Prior context
Dig through old files and copy last year's ad by hand.
Retrieve structured prior-year history; separate reusable patterns from stale facts.
Copy generation
Ask a chatbot for the final ads and trust whatever comes back.
Seed from approved patterns; AI is optional; deterministic validation is required.
Quality control
Catch errors during manual review — or after the import fails.
Block over-length, duplicates, stale dates, internal tokens, and banned terms before output.
Bulk execution
Hand-build spreadsheets and fix import errors row by row.
Generate a tested, correctly-mapped Google Ads Editor CSV with diagnostics.
API actions
Let an agent write straight to the live Google Ads account.
Show a dry-run evidence packet — readiness, paused state, exact ops — and require human confirm.
You'll run the governed version end to end with a fictional advertiser — Boltwright & Co., an online tools & hardware store — and fully synthetic data.