We build so the AI horror stories don’t happen to you.
Most businesses adopt AI faster than they secure it. The result is the stories you have read: leaked client data, a confident wrong answer sent to a customer, a tool that quietly trained on everything you fed it. We engineer the boring safeguards that keep those stories from being yours.
A true-to-life scenario
An employee pastes a client contract into a free chatbot to summarize it. That contract is now in a third party’s system, possibly in a training set. Nobody decided this. Nobody logged it. You find out when the client asks.
Every safeguard below exists to make that impossible by design, not by asking people to be careful.
The production harness
Five layers wrap every system we ship. None of them are optional, and none of them are visible to your customers. That is the point.
Vendor and contract
Commercial API tiers with contractual no-training terms and data-processing agreements. Your data is never used to train anyone’s model.
Data minimization
The system only ever sees the data it needs. We strip, redact, and scope inputs before they reach a model.
Infrastructure
Everything runs in your own cloud account, defined as infrastructure-as-code. You can audit it, redeploy it, or shut it down without us.
Prompt and output
Structured input and output at every model call, with validation, so the system never blindly trusts what a model returns. This is the defense against prompt injection and unsafe output handling.
Observability and audit
Every model call is logged and auditable. If something goes wrong, you can see exactly what happened and when.
The discipline behind every build
Security is not a feature we add at the end. It is how the work is done from the first call.
The standards we build to
Not invented checklists. The recognized frameworks for AI risk, security, and professional confidentiality.
- NIST AI RMF
- The U.S. risk-management framework for AI. We build and assess against it.
- OWASP LLM Top 10
- The standard list of the ten most common large-language-model security risks. We test for all ten.
- ABA Rule 1.6 + Formal Opinion 512
- The confidentiality bar for legal and professional-services work. A commercial API with no-training terms, audit logs, and your own infrastructure meets the "reasonable precautions" standard. Consumer chatbots do not.
- AICPA SSTS 1.4
- The standard relevant to accounting and tax work.
One honest note: we are not SOC 2 certified, and we will tell you plainly when a control is outside our scope. Architecture is something we can promise. A certification we do not hold is not.
Your options, honestly
There are three ways to get serious AI built. We will tell you when we are not the cheapest, because we are usually not the point of comparison anyway.
Hire a senior AI engineer
A six-figure commitment, and they only know what they know. They go on vacation. They leave.
Hire a large agency
You become one of fifty accounts, and the senior people from the sales call are not the ones doing your work.
Work with us
The same outcomes, senior-built from first call to final handoff, no hiring risk, and you own the result.
Same outcomes. A fraction of the cost. No hiring risk. And the code lives in your repository, so you are never locked in.
Want your current AI use stress-tested?
We will tell you where the risk is before it finds you. A 30-minute call is enough to start.
Or send us a note at [email protected]