HACKER Q&A
📣 legitimate_key

How do founders demo real product without exposing sensitive data?


Pitching soon and want to show the real thing, not a sanitized environment. How do you handle sensitive during live demos?

The problem: investors want to see your actual product working with real data, but showing real dashboards means exposing credentials, API keys, client data, or internal systems on a shared screen.

The usual options all have problems: - Demo environment with fake data → looks staged, kills credibility - Real product with real data → security risk, one screenshot away from an incident - Pre-recorded walkthrough → can't answer specific questions or show interactivity

Curious how others handle this. Do you just accept the risk? Build sophisticated demo infrastructure? Something else entirely?

  👤 efortis Accepted Answer ✓
I’ve used (and wrote) https://mockaton.com for this. It has a browser extension, which downloads all API responses in your flow.

then you can run mockaton with those mocks. you’ll manually have to anonymize sensitive parts though.

also, you can compile your Frontend(s) and copy their assets, so yo can deploy a standalone demo server. see the last section of: https://mockaton.com/motivation

mocks don’t have to be fully static, it supports function mocks, which are http handlers.

for demoing, the dashboard has a feature for bulk selecting mocks by a comment tag.

👤 gnatman
Surely real product with fake data is the answer. Fake data doesn’t necessarily mean “silly” data e.g. names like Larry Llama or myfaketestwebsite.com. There’s no reason why your real product running on sandboxed data should hurt your credibility.
👤 rekabis
At my last job they had an entire section of the product - hidden behind feature flags and enableable only in development - whose sole purpose was to generate dummy content for the different sections of the product. When I left, they were extending it with AI integration to have it generate more realistic data. The overall program - when in prod - contained massive amounts of PPI/PII, so we needed a way to generate massive amounts of realistic-looking dummy data to stress test it while in dev.