orgadmin.ai

Data Seeding

Salesforce sandbox seeding with built-in data masking

Select objects and filters from a source org, apply field-level masking rules to protect PII, and load realistic test data into a sandbox — in the right order, with relationships intact, as a resumable background job.

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UAT needs data shaped like production, and production data is full of real people. The plan before it runs: 5 related objects, 1,120 records, and 14 masked fields across them — Contact alone accounts for five, because that is where the personal data is. Nothing is written until the preview matches the plan, which is the line at the bottom.

What you can do

  • Pick objects with SOQL filters: seed exactly the slice of data you need
  • Automatic PII detection flags emails, phones, addresses, and identity fields
  • Masking strategies per field: hash, redact, scramble, replace, randomise in range, shift dates
  • Relationship-aware loading: parents before children, with old→new ID remapping
  • Dry runs to test a plan end-to-end without loading anything
  • Reusable seeding plans and resumable, cancellable background runs

How it works

1

Build a plan

Choose objects, filters, and masking rules: the PII detector suggests fields you shouldn’t copy raw.

2

Dry run

Extract and transform without loading, and check the counts and masking manifest.

3

Seed the sandbox

Detached background job with progress you can watch, leave, and resume. The target must be a sandbox — production is refused.

Why it's different

Masking you cannot switch off

Field-level transforms are applied before data leaves the source org, the run stores a manifest of which strategy hit which field (never the values), and the loader refuses production targets outright. Compliance by construction.

Try asking

  • Give every developer sandbox realistic accounts, opportunities, and cases
  • Refresh UAT with current production-shaped data — minus the real PII
  • Reproduce a data-dependent bug safely
  • Stand up demo environments with masked but realistic data

Data Seeding — questions

No. The target is validated live at run start and must be a sandbox. Production is refused by design.

The relationship graph is discovered automatically, objects load in dependency order, and source→target ID mappings re-link children to their new parents.

Works even better with

Data Loader

Paste from Excel, map, preview, run.

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File Backup

Find every file, see what it is attached to, export the lot as a browsable ZIP.

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Deployments

Diff two orgs. Pick what ships.

Learn more

Replacing something?

  • orgadmin.ai vs Prodly

    Purpose-built for CPQ configuration data. Compare when what you actually need is realistic sandbox data with PII masked.

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Put Data Seeding to work on your org

Every AI feature on your own provider key, from A$14.99 per user per month.

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  • 14-day free trial
  • No credit card required
  • Cancel any time