Why BreachIQ exists

Analysts read, watch and certify, then meet their first real incident with no reps in the decisions that matter: what to contain, what to escalate, what to leave alone, and when to say you do not know enough yet. Nothing in that path produces evidence that judgement is improving.

BreachIQ turns that into repetition you can measure. Realistic incidents are generated and adjudicated by AI, every decision is scored against an authored rubric, and the result moves a skill map instead of a completion bar.

A scenario opens as a live incident: a clock, a stream of evidence, and choices that change what happens next. You act — request evidence, contain, escalate, communicate — and the simulation responds.

Adjudication happens against grounded reference material rather than model recall. In the debrief, each decision carries a verdict and the evidence behind it, and you can contest a call you disagree with. Contested cases are reviewed and feed back into scenario quality. Scored runs shift a competency map across six axes, and the next incident is chosen to work on the weakest one.

BreachIQ is built by Mircea Neagu. Twenty years in the automotive industry, across execution and leadership roles, taught the habit the product is built on: outcomes are decided by the quality of decisions made with imperfect information, and decision quality can be trained.

He joined the AI revolution at the end of 2025 and now builds applications intended to add real customer value, including NextLeadium and BreachIQ.

To be plain about it: he is an experienced engineering and technology leader and an AI-native product builder — not a practising cybersecurity analyst. Scenario content and scoring rubrics are authored to be checked and challenged by practitioners, and the founder beta exists precisely so people who do the work every day can tell us where the simulation is wrong. If you find something that does not hold up, write to contact@breachiq.ai.

• The learner decides. AI generates, adjudicates and coaches. It never acts on real systems on anyone's behalf.
• Everything is synthetic. Incidents, logs, alerts, artefacts and personas are invented. No real customer, employee or third-party data enters a simulation.
• Defensive only. Attacker behaviour is modelled at the level required for defensive learning — tactics, indicators, artefacts — and stops short of working exploit code or operational instructions against real systems.
• No pretending. AI-generated content is never presented as human-authored, and you can ask why a decision was scored the way it was.
• Your data is yours. Performance data belongs to the learner; sharing it with anyone else, including an employer, requires explicit opt-in. See the Privacy Notice.

BreachIQ is in founder beta and invite-only. The scenario library, live simulation, adjudicated debrief and skill map are working; the product is being built with a small group of practitioners rather than for an imagined one. No payment is taken during the beta.

Create an account and ask for a seat, or see plans and pricing.