DarkFindR LogoDarkFindR

Built from real incidents

not theoretical threat models

DarkFindR didn't start as a product idea.

It started in post-incident situations, where organizations urgently needed to understand what was actually exposed, and what decisions they could stand behind.

The gap most organizations only see after the breach

Most security teams are not short on tools. They are short on decision-ready intelligence

In practice, we consistently observed:

  • Limited visibility into what data is truly exposed on the Dark Web
  • Difficulty separating real exposure from noise
  • Investigations that rely heavily on manual effort
  • Results that are slow, partial, and hard to defend

The consequence is predictable:

Security teams are forced to react without full clarity, often under executive and regulatory pressure

From advisory work to the limits of monitoring

DarkFindR originated within Wannath, a cybersecurity consulting firm known for its work in governance, risk, compliance, and post-incident response.

For years, Wannath teams supported organizations after cyberattacks, using traditional advisory methods and existing Dark Web monitoring tools to investigate potential data exposure.

Those tools helped surface signals. They did not provide answers.

The limitations became clear:

  • Investigations were slow and resource-intensive
  • Results varied depending on analyst expertise
  • Findings were difficult to reproduce or scale
  • Human effort remained the bottleneck
Clients asked a straightforward question: Why is it still so hard to get a clear, reliable answer?

A required shift: from expert-driven services to scalable intelligence

At that point, the conclusion was unavoidable: this problem could not be solved by adding more consultants or more dashboards.

What was needed was a structural change: from expert-driven investigations to technology-driven exposure intelligence.

The goal was clear:

  • Automate Dark Web data collection
  • Reduce dependency on manual analysis
  • Qualify exposure with consistency and precision
  • Deliver results fast enough to support real decisions

Advances in automation and artificial intelligence made this approach viable. DarkFindR was designed to turn those capabilities into operational intelligence, not abstract signals.

Advances in automation and artificial intelligence made this approach viable. DarkFindR was designed to turn those capabilities into operational intelligence, not abstract signals.

What DarkFindR is built to do

DarkFindR addresses a specific failure in traditional Dark Web monitoring: signals are detected, but exposure is not clearly qualified.

Instead of adding another layer of alerts, DarkFindR focuses on:

  • Identifying what data is actually exposed
  • Putting that exposure into context
  • Supporting decisions that can be justified to executives, auditors, and regulators
This is not monitoring for awareness. It is Dark Web exposure intelligence built for accountability.

A team shaped by real operational constraints

DarkFindR was founded by Erwan Bouvier, a cybersecurity professional with more than 25 years of experience across industry and services.

Picture of Erwan Bouvier

Erwan Bouvier is a cybersecurity professional with over 25 years of experience across industry and services.

A graduate of INSA Rennes, Erwan spent much of his career working in complex security environments before turning to entrepreneurship.

The DarkFindR Team

The DarkFindR team brings together consultants and engineers with a shared background in:

  • Post-incident investigations
  • High-pressure operational environments
  • Governance- and compliance-driven security

This background directly shapes how the product is built with rigor, traceability, and long-term reliability as core principles.

A structured and sovereign foundation

To support the development of DarkFindR, a dedicated spin-off, Quiet Mind, was created to carry the project.

2024

1

Incubated within CyberBooster

2025

2

Selected by the Prime Minister's Office as part of the national cybersecurity program

This framework reflects a clear commitment to:

High security standards
Regulatory alignment
European technological sovereignty

DarkFindR is designed for regulated environments by design, not by adaptation.

Dark Web intelligence should reduce uncertainty, not increase it.

No generic demo. You see your real exposure, in real time.
We analyse your own exposure, in real time
Book your 30-minute live demo
Why now ?NIS2 is acceleratingWith AI, attacks are never been so efficient
Your Dark Web monitoring cannot stay reactiveDarkFindR makes anticipation operational today