How AI Turned A Boring Idea Into a Digital Product in 20mins
A 4-hour audit-preparation task became a digital product in under 20 minutes.

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How AI Turned A Boring Idea Into a Digital Product in 20mins
A 4-hour audit-preparation task became a digital product in under 20 minutes.

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Three days ago, I noticed a recurring problem in the compliance world.
Companies spend weeks preparing for SOC 2 and ISO 27001 audits, yet many teams still review authentication logs manually when auditors request evidence.
Twenty minutes later, I had built a working digital product.
Preparing for a SOC 2 or ISO 27001 audit sounds straightforward until someone asks:
“Can you provide evidence that authentication activity is being monitored and reviewed?”
That’s when many teams discover they’re sitting on thousands of lines of raw authentication logs.
If you’d like to try the tool, there’s a free trial available here:
The Problem With Manual Log Reviews
For small SaaS teams and IT administrators, authentication logs usually live in places like:
/var/log/auth.log- SSH access logs
- Linux authentication records
- Server access logs
When auditors request evidence, the typical process looks like this:
- Export logs from servers
- Open them in a text editor
- Search for failed logins
- Identify suspicious IPs
- Count repeated login attempts
The process works.
But it can easily consume several hours every audit cycle.
What Auditors Usually Want To See
Below are a few screenshots from the application.
Try the free trial:

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In most cases, auditors are not interested in reading thousands of raw log entries.
They want evidence showing:
- Failed login attempts
- Successful authentications
- User access activity
- Suspicious authentication events
- Repeated login failures
- Indicators of brute-force attempts
The challenge is converting raw logs into something understandable.
Example: Finding Brute-Force Activity
Imagine your authentication logs contain entries like:
Failed password for admin from 203.0.113.5
Failed password for admin from 203.0.113.5
Failed password for admin from 203.0.113.5
Failed password for admin from 203.0.113.5
A human reviewer immediately sees the pattern.
But identifying dozens of similar patterns across months of logs becomes tedious and error-prone.
What We Actually Need
Instead of reading logs line-by-line, we need a way to:
- Detect repeated login failures
- Group events by IP address
- Highlight authentication anomalies
- Generate structured reports
- Export evidence for auditors
Ideally without deploying a SIEM.
Why Not Just Use Splunk or Elastic?
Tools like Splunk and Elastic are excellent for security monitoring.
However, many smaller organizations preparing for audits need something much simpler:
- No infrastructure
- No ingestion pipelines
- No cloud setup
- No recurring subscription costs
Sometimes the goal is simply:
Load logs → Analyze → Export evidence
The Tool I Built
There’s a free trial available, and everything runs locally with no data leaving your machine.
After repeatedly performing manual authentication log reviews, I built a small desktop application that converts raw authentication logs into audit-ready reports.
It can:
- Detect failed and repeated login attempts
- Identify potential brute-force activity
- Highlight authentication anomalies
- Track user access behavior
- Export structured Excel and CSV reports
- Work completely offline
Because it runs locally, no log data leaves your machine.
Typical Workflow
- Export authentication logs
- Load them into the application
- Click Analyse
- Export audit-ready reports
The entire process usually takes only a few minutes.
Final Thoughts
If you’ve ever spent an afternoon manually reviewing authentication logs just to produce audit evidence, you already know the bottleneck isn’t collecting logs.
It’s turning them into something auditors can actually use.
That’s the problem I wanted to solve.
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