01 — The Problem

Enterprises lose millions to process leaks they cannot see

Process bottlenecks, regulatory gaps, and recurring failures are buried across departments. There is no systematic way to discover them, no way to quantify them, and no one accountable for finding them.


By the Numbers

The scale of invisible operational loss

€2M
Average annual hidden cost

The typical enterprise loses €500K–€2M per year to invisible process leaks — bottlenecks buried in logs, tickets, and handoff gaps nobody questions.

78%
Enterprises fear AI data leaks

Security teams block adoption. Compliance prohibits cloud uploads. Innovation stalls while competitors move forward with sovereign alternatives.

10×
Cost multiplier for late discovery

Problems found late cost an order of magnitude more to fix. Traditional consultants take months to diagnose what automated analysis surfaces in hours.


Root Causes

Where process leaks originate

Four systemic patterns that allow operational friction to persist undetected across business units.

Invisible Bottlenecks

Critical inefficiencies hidden inside server logs, ERP exports, and ticketing systems that no one is actively monitoring for process-level patterns.

  • Recurring IT tickets nobody correlates
  • Manual handoff steps embedded in workflows
  • Undocumented workarounds that mask failures

Regulatory Lag

Compliance frameworks evolve faster than internal policy reviews. The gap between AI Act, NIS2, DORA requirements and actual practice widens silently.

  • Policies written once, never re-validated
  • Gap analysis done manually, if at all
  • Audit findings arrive too late to prevent cost

Post-Project Amnesia

Lessons from completed projects are documented but never cross-referenced. The same failure patterns repeat across teams, divisions, and years.

  • Post-mortems filed and forgotten
  • No pattern matching across project history
  • New teams repeat predecessors' mistakes

The AI Trust Gap

Enterprises know AI could find these problems — but uploading sensitive operational data to public AI platforms is a non-starter for security and compliance.

  • Public AI trains on uploaded data
  • Security teams rightfully block adoption
  • Result: problems persist, competitors advance

Next Step

See how LeakDetect solves this

A sovereign pipeline that turns unstructured data into quantified problems and automated fixes.

View the Process Request Audit