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One silent failure cost us 6 hours of revenue. One alert pays for a year of NotiLens.

Six hours.

That's how long our payment webhook was silently failing before a user messaged us.

We were running a creator marketplace and payments had been failing for hours. No error in the logs. No crash. No alert. Just a customer asking why their payment wasn't going through.

We had error monitoring, uptime checks, the usual stack. None of it caught this.

Because the server was up. The endpoint was responding. Everything looked fine.

The webhook was just quietly dropping events into a void.


That night we started building what we wished existed - something that watches for silence, not just noise.

Not "did it crash?" but "did it actually do anything?"

Six months of using it internally, catching failures before users did, we decided to productize it.

That's NotiLens.


Three failures it's caught since we started dogfooding:

  1. Cron job ran at 3am. Exited successfully. Processed 0 records. Database connection had silently timed out. Found out via NotiLens at 3:04am - not from support tickets at 9am.

  2. AI agent looped 14 times in 6 minutes. No output. API credits burning. NotiLens detected the loop pattern and fired before the bill did.

  3. Signup flow dropped to zero for 4 hours on a Tuesday afternoon. Not a server issue - a misconfigured Cloudflare rule. Revenue just stopped. NotiLens caught the silence in 20 minutes.

None of those threw an error.


Early users are catching things too:

  • A solo founder running an AI agent pipeline catching loops before users complained

  • An agency owner fixing a broken Zapier node before their client ever knew

  • A backend engineer catching a skipped ETL step at 2am before anyone noticed

None of those threw an error either.


What we're building toward:

The monitoring layer for the parts of your backend that don't crash - they just quietly stop working.

Currently live. Looking for founders who've been here before to try it and tell me where it breaks.

notilens.com

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