Build Your Own Simulations and Security Awareness Training
One engine, both halves, run by your own security team. Mapped to the threats in play right now, not the ones a vendor wrote about last year.
Breacher.ai is a simulation and awareness training engine for security teams. Describe a scenario and it builds the campaign: Teams impersonation, deepfake video, voice phishing, QR, email, SMS. Point it at what that campaign found, or at one of your own policies, and it builds the training. Minutes either way, and both are yours to edit and keep.
Your team runs the program. Managed delivery stays available as a separately priced mode.
Three ways into a module: generate it from what the simulation found, generate it from a policy document, or start from scratch.
Authoring is table stakes now
Producing content used to take time, which is why it was the part you were billed for. That part is over.
The content moat is gone
A branded, role-specific module is minutes of compute now. Every vendor in this category can do it, including us, which is exactly why it cannot be the product.
Platform choice did not predict outcomes
Across our engagements, the platform an organization already had did not predict how it performed under simulation. What tracked was how seriously they invested in security at all. Observational, not controlled.
Detection decays, procedure does not
Spotting a fake gets harder with every model release. A callback to a number from your own directory works the same whether the caller was synthetic or real. That is the control worth training.
What does not commoditize
OSES™ runs the simulation, scores what happened, and generates the awareness training on demand, aligned to your own policy, procedure, and process. Every target lands somewhere on the ladder, and the ladder is the spine of the score.
The share of targets who completed a consequential action: an outbound payment, a vendor banking detail change, a credential reset, an MFA enrollment or reset, a privileged access grant, software installed on request, data exported or disclosed, physical access granted. The click is where a phishing test ends. It is where an incident starts.
Coverage is the share of consequential actions that carry a channel-independent verification requirement at all. Hold rate is whether that requirement actually executes when someone is under pressure from a voice they recognize. The gap between the two is the finding, and the exception rate is the bound on it.
Two terms, deliberately. DEPTH is how far the worst single case progressed up the ladder. SPREAD is weighted population incidence. One organization can fail deep and narrow, another shallow and wide, and the remediation for those is not the same. Reported as a banded score rather than a percentage with no context.
Shipped as a capability, not sold as a library
The differentiator is not that the engine writes content. It is that the content is generated from what your own people actually failed, that it targets the procedure rather than the tell, and that you own it when we are finished.
Describe the scenario in plain language and the concierge drafts the playbook, assigns a persona, selects or clones the voice, places the call, and handles the inbound callback. Every object it creates stays editable, including the prompt behind the agent.
The full program
A curriculum, or an engine you own
The two models disagree about what you are actually buying, and the disagreement shows up in the line item.
Teams that would rather own the program
If your executives are worth impersonating and your finance team can move money on a phone call, a curriculum you rent is leaving the expensive part of the organization untested.
What leaders say after a cycle
Users were surprised with how good the Deepfakes were, I'm really impressed. Really crazy talking to a Deepfake.
I was expecting a Demo, not an episode of Black Mirror. This is really good, I'm surprised at how advanced it's gotten.
The entire company is already talking about voice cloning and the risks. It's been a huge win for us already, without even seeing any of the actual results.
The training was well-structured, clear, and provided valuable insights into the growing threat landscape associated with deepfakes.
Common questions
What is OSES™ and how does it drive the training?
OSES™ is Orchestrated Social Engineering Simulation, our simulation methodology. A coordinated multi-channel sequence runs first and is followed through to the consequential action. Training is then generated against what that sequence actually found, so the module lands against a real failure in your process rather than a hypothetical one, and the same sequence can be run again to measure whether anything changed.
Does the awareness platform we already use matter?
In our engagement data, the awareness platform an organization already had in place did not predict how that organization performed under simulation. A legacy platform produced both the best and the worst results we observed. What appeared to track with outcomes was how seriously the organization invested in security generally. That is an observation from our own book rather than a controlled study, and it is a statement about content delivery tooling, not about simulation and measurement tooling, which are different products.
Are you saying awareness training is worthless?
No. The narrow claim is that detection-based training for deepfakes and synthetic media loses value every time generation quality improves, because it asks a person to spot something that is getting harder to spot. Awareness training in general has real value and we support it. What we argue for is training that targets the procedure, which does not decay, rather than the tell, which does.
Why don't you sell a content library?
Because AI has collapsed the cost of producing a competent, branded, role-specific module to near zero, and we are not going to charge you for something that is no longer scarce. Compliance curriculum breadth and certificate volume are the incumbents' assets. We ship authoring as a capability and sell access to the engine and the measurement instead.
Who actually builds the training modules?
Your team does, from inside the platform. Point the builder at the playbook someone just acted on and it drafts the remediation module around what they missed. Drop in a policy, AUP, or code of conduct and it drafts the slides and the knowledge check. Output is SCORM, so it drops into the LMS you already run, branded as yours. There is no content request queue and no professional services line item to write a course.
Can we push results into the systems we already use?
Yes. Everything the console does is available through the REST API, and campaign and outcome events fire as webhooks, so results can land in your LMS, SIEM, GRC platform, or reporting stack without anyone exporting a spreadsheet. Training modules leave as SCORM for the same reason. If a system can accept a webhook or a REST call, it can take this data.
What do you actually measure?
Every target lands on an engagement ladder from L0, no action, to L4, a consequential action completed. On top of that: action rate, the share of targets who completed a consequential action; verification coverage, the share of those actions that carried a channel-independent verification requirement; process hold rate, whether that requirement actually executed under pressure; exception rate; and the DEPTH and SPREAD terms of the OSES™ score, which report how far the worst single case travelled and how much of the population went with it.
Can you benchmark us against our sector?
Only where we have enough customers in that sector to produce a defensible median, and for most sectors we do not yet. We will tell you whether we can produce a peer comparison for your vertical before you buy rather than after. Where we cannot, the measurement is still your own baseline against your own re-test, which is the number that matters most anyway.
Do you report on individual employees?
No. Reporting is organizational, with no named individuals and no department leaderboards. Training is targeted where the simulation found a gap, but the findings a leader sees describe the organization and the process, not a list of people who failed.
Do we need consent to clone an executive voice or likeness?
Yes. Consent and scoping are agreed in writing before any voice or likeness is built, every engagement runs under signed authorization, and generated voice and video are handled with zero retention. Sources used for the contextual layer are recorded so every pretext is traceable back to public material.
Who runs the program day to day?
You do. Your team runs the cycle from the console: building the campaign, reviewing findings, generating the modules, and releasing them. Nothing is installed, everything runs externally, and directory sync from Microsoft Entra ID is optional and directory-only. If you would rather hand delivery over entirely, that is our Managed delivery mode and it is priced separately.
Will this satisfy our auditors and insurers?
The program produces third-party evidence of what was tested, what failed, what training was delivered, and what changed on re-test, in a format written for auditors and insurers rather than reformatted afterwards. It supports frameworks including NIS2, DORA, and SOC 2.
Find out whether your process holds
Thirty minutes. We build a campaign live from a plain-language brief, run it through to a consequential action, and show you the score that comes out the other side. The module it writes on the way is yours to keep.
Want us to run it instead? That is Managed delivery. Or see the micro module format.
support@breacher.ai
