Bulk repricing with rules
Reprice by tag, collection, vendor or margin: computed from cost data, guarded by floors, applied only after you read the diff.
See the template →Past a certain catalog size, bulk edits stop being edits and become engineering: rate limits, retries, partial failures. Collaudo writes and runs that engineering for you: on AWS infrastructure in eu-central-1, rehearsed before it touches anything.
Reprice by tag, collection, vendor or margin: computed from cost data, guarded by floors, applied only after you read the diff.
See the template →Round every price to .99 or .90 across the whole catalog without ever producing a price below your margin floor.
See the template →Find every variant missing a unit cost: the rows that silently break every margin calculation you'll ever run.
See the template →Keep budget / mid / premium bands up to date automatically as prices move, for filters, feeds and analytics.
See the template →A nightly pass over every variant, tagging what is about to run out. No event needed, no product forgotten.
See the template →Bulk operations, throttling, retries and resumption are part of the runtime, not your problem. The report tells you what ran, how long it took, and what was skipped.
100,000 variants read in minutes. Every write captured, none applied until you approve. How the dry run works →
The runtime uses bulk operations where possible and throttles, retries and resumes everywhere else. That plumbing is part of the platform: your automation describes the rule, the runtime worries about the limits.
The dry run makes 'halfway' visible before it can hurt: the whole job executes against real data with writes held, so failures show up in the rehearsal, not the store. Live runs are logged item by item, so a partial run is a report you can read, not a mystery.
It runs on AWS (eu-central-1), built for heavy catalogs. Our demo store runs Collaudo at a six-figure variant count. We designed the dry-run report around that scale.
Describe the job, watch the AI build it, rehearse it, deploy it.
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