Cybersecurity

Self-learning AI Security Dashboard

An AI that scans an enterprise's infrastructure 24/7, detects threats, and continuously retrains itself.

24/7 Non-stop scanning
-87% Manual work
< 3 min To first detection

The problem

The pain the client was dealing with before we started.

  • Scans and findings were spread across 7 different tools and export files.
  • Security team lost 15+ hours per week on manual reporting and copy-paste work.
  • Threats were only spotted hours later because context was missing.
  • Management reports were inconsistent and required repeated manual work.

What we built

Built around their exact workflow, not an off-the-shelf product.

  • Central AI dashboard that automatically normalizes and correlates data from all security tools.
  • Machine learning model that continuously learns which findings are actually relevant.
  • Automatic prioritization based on asset value, exploitability, and historical context.
  • Real-time Slack/Teams notifications for critical findings.
  • One-click executive reports in a consistent format — no manual work.

How it works

The process in four steps.

1

Collect

APIs collect scan data from all tools in real time.

2

Normalize

Data is converted to one unified data model.

3

Learn

AI scores findings based on history and feedback.

4

Act

Priority findings instantly trigger alerts and tickets.

Results & impact

Time saved, money saved, and lifetime value.

Time Saved

15 hours per week saved — ~780 hours per year of senior FTE capacity.

Cost Savings

€78,000 per year in direct labor costs, excluding prevented incidents.

Detection Speed

From 4+ hours to under 3 minutes between scan and first alert.

Self-improving

False-positive rate dropped from 34% to 8% in 6 months.

Lifetime Value

One implementation, ongoing value. Gets better every month at no extra cost.

Tech stack

The tools we used.

Python FastAPI PostgreSQL OpenAI API Elasticsearch Docker

Want this for your business?

Book a free 30-minute call.