GoMask.ai

GoMask.ai

Instant compliant test data for engineering teams

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Test data bottlenecks kill velocity. Teams wait days for data refreshes or secretly use production. GoMask delivers instant, compliant test data through schema-aware masking and AI synthesis. Minutes, not days. Compliance built-in, not bolted on.
This is the 2nd launch from GoMask.ai. View more

GoMask as Code

Test data as code: YAML rules, Git versioned, & CI/CD ready
GoMask as Code brings test data management into your Git workflow. Define masking rules in YAML, commit alongside your schema, and deploy through GitHub Actions, GitLab CI, or Jenkins. No more waiting for test data refreshes. No more tickets. No more compliance gaps. Schema changes and data rules travel together in a single commit. Every change is version-controlled and audit-ready.
GoMask as Code gallery image
GoMask as Code gallery image
GoMask as Code gallery image
GoMask as Code gallery image
GoMask as Code gallery image
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Launch tags:Productivity•SaaS•Developer Tools
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agent by Firecrawl
agent by Firecrawl
Gather structured data wherever it lives on the web
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What do you think? …

Alex Hayward
GoMask.ai
Maker
đź“Ś
We built GoMask as Code because our own team kept asking for it. We already had a platform for safe test data. But developers on the team didn't want to touch the UI. They wanted masking rules in YAML, sat next to schema definitions, deployed through the same pipeline as everything else. We talked to data engineers on Reddit about how they handle test data. Top response was brutal: "Everywhere I've worked with sensitive data, everybody ended up secretly working off prod." Not because they're reckless. The safe path just takes too long. Tickets, waiting, manual refresh cycles. GoMask as Code cuts that out. Rules in YAML, committed to Git, deployed automatically. Safe test data without the bottleneck. Questions about config or setup? Drop them below. Also please let us know your feedback.
Masum Parvej

@alex_hayward1 YAML‑based configs reduce UI friction, though I wonder how non‑engineers will collaborate on rule changes.

Alex Hayward
GoMask.ai
Maker

@masump great question! GoMask has both as code and UI options in the platform so non-engineers can use the UI alongside those who prefer code. We really wanted to build in collaboration for all personas!

Natalija Kerstein

@alex_hayward1Hey!
I was reading through GoMask.ai’s Privacy Policy, it’s actually very well structured and clear, especially around security and data retention

Just a small heads-up in case it’s useful: since you’re processing potentially sensitive customer datasets and using multiple analytics/CRM tools, it might be worth double-checking a few compliance details.. like explicitly naming the lawful basis per processing purpose (GDPR Art. 6), tightening cookie/analytics consent language, and clarifying safeguards for international transfers beyond SCCs (especially with US-based tools).

Totally possible this is already covered elsewhere or planned, just wanted to flag it early since it’s an area that can become risky as you scale.

Raju Singh

Brilliant approach to test data management! Defining masking rules in YAML and managing them via Git workflow is perfect for DevOps practices. The compliance-first mindset is exactly what enterprises need. This would be invaluable for automated testing in ITSM platforms. Great execution!

Alex Hayward
GoMask.ai
Maker

@imraju Thank you so much for the comment!! There is a free account option at gomask.ai. Have a go with it and see what you think. We would love the feedback!