Security Architecture
The controls we implement in AI systems: isolation, permissions, secrets, logging and prompt-injection defence.
Open pageSecurity review is where most AI projects stall. These pages say what we implement, what we can show, and what we do not hold — so a procurement team can check rather than trust a badge.
Introduction transcript. Client: How do I know I can trust the system? Qubi: Let me show you my working. Qubi: Documented controls. Traceable decisions. Evidence your team can check. Client: No shiny badge doing all the talking? Qubi: Just the things we can actually show you. Qubi: Bring your questions. I’ve saved you a seat.
We do not currently hold SOC 2, ISO 27001 or HIPAA certification.
Most agency sites in this space display those badges as design elements. We would rather tell you plainly, because a vendor claim you cannot verify is worth less than an honest one — and because procurement will check.
What we do is implement the controls those frameworks describe, document them per engagement, and build systems that generate the evidence your auditors need. Clients who hold certifications we do not can still use us: the systems we build are designed to sit inside their certified scope.
When we complete a certification, it will appear here with its audit date and scope, and in the machine-readable version of this site. Until then, this page says what is true.
Each row is a claim a procurement team can check, with the status it carries today.
We do not currently hold SOC 2, ISO 27001 or HIPAA certification. Any certification we complete will appear on this site with its audit date and scope.
The controls we implement in every AI system we build.
Retrieved content is designed to be treated as untrusted data rather than as instructions. Tools carry the minimum permission needed, destructive operations require confirmation, and retrieved content cannot authorise a subsequent tool call. Filtering helps at the margin but cannot be the primary control.
We document them per engagement, and build systems that generate the evidence your auditors need.
Where the provider offers it, we use enterprise endpoints configured for zero retention and no training on inputs — at the time of writing, and confirmed against the provider’s current terms per engagement. Zero retention is at the provider; your own logs stay in your infrastructure under your retention policy.
EU regions for EU data residency, your own VPC where that is required, or entirely on your hardware with open-weight models where nothing may leave the perimeter. The requirement is captured in discovery because it constrains model selection.
Code in your repositories, infrastructure in your accounts, any fine-tuned weights yours. No proprietary platform and no runtime dependency on us.
Every third party in the processing path, including model providers, disclosed with role and region. No unnamed “trusted partners”.
Yes, and we can work from your paper. Standard contractual clauses where a transfer requires them. For engagements where we never hold your data, we say so rather than papering over a processing relationship that does not exist.
Where a control is not in place, the response says so. We would rather lose a deal on a truthful answer than win one on a carefully worded almost-yes.
Third-party terms are stated at the time of writing. We confirm them against the provider’s current terms for each engagement.
Isolation, permissions, secrets handling, logging and prompt-injection defence — the controls we implement in every AI system we build.
Lawful basis, residency, sub-processors and subject rights when a language model sits in the processing path.
Risk tiers, GPAI obligations and timelines — what deploying an AI system in the EU now actually requires.
Where the provider offers it, we use enterprise model endpoints configured for zero retention and no training on inputs — at the time of writing; we confirm the provider’s current terms per engagement — and state the exact configuration in the architecture document. Zero retention is at the provider; your own logs stay in your infrastructure under your retention policy.
Code in your repositories, infrastructure in your accounts, any fine-tuned weights yours. No proprietary platform and no runtime dependency on us.
Every third party in the processing path, including model providers, disclosed with role and region. No unnamed “trusted partners”.
Where a control is not in place, the response says so. We would rather lose a deal on a truthful answer than win one on a carefully worded almost-yes.
Facts about how we work, not measured client outcomes.
If it is a hard gate in your procurement policy, no — and we would tell you that on the first call rather than in week six. Some organisations can accept a risk exception for a small engineering supplier with documented controls; that is a decision for your risk function, not something we would try to argue you into.
Wherever your requirements dictate. EU regions for EU data residency, your own VPC where that is required, or entirely on your hardware with open-weight models where nothing may leave the perimeter. The residency requirement is captured in discovery because it constrains model selection, and discovering it late causes rework.
As an authorisation problem, not a filtering one. Retrieved content — documents, tickets, web pages, emails — is designed to be treated as untrusted data rather than as instructions. Tools carry the minimum permission needed, destructive operations require confirmation, and the design does not allow retrieved content to authorise a subsequent tool call. Filtering helps at the margin but cannot be the primary control.
Yes, and we can work from your paper. Standard contractual clauses where a transfer requires them. For engagements where we never hold your data — systems running entirely in your infrastructure — we will say so rather than papering over a processing relationship that does not exist.
The controls we implement in AI systems: isolation, permissions, secrets, logging and prompt-injection defence.
Open pageLawful basis, data residency and subject rights when an LLM is in the processing path.
Open pageRisk tiers, GPAI obligations and timelines — what deploying an AI system in the EU now requires.
Open pageWhere data physically sits, who can compel access to it, and how each hosting choice changes the answer.
Open pageThe vendors that may process personal data on our behalf, and why your system's providers are contracted by you.
Open pageWho trained a model, who operates it, what its licence permits, and how to evaluate a model you did not build.
Open pageWhat our data processing agreement says in plain English, when it is needed, and what we will and will not sign.
Open pageOur standing answers to the questions every enterprise security review asks, published so you do not have to send the spreadsheet.
Open page
What we built, what stage it is at, and a link to the live thing wherever there is one.
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Website, backend and app assets for Sonora, a free AI sound-therapy app on iOS and Android published by Cognitive AI.
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Live at coherence.com: brand identity generated with AI agents we directed, the motion system and website for the group behind Sonora, AboutAI, WakeUp and MudShadows. Agent work remains in build.
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Apps, platforms and campaigns for these teams, long before the AI work. Every one is written up on the work page — what we did, and where our part ended.
Tell us the job you would hand over if you trusted a machine with it. In one 30-minute call we will tell you whether it should, what it would take — and if it should not, we will say so.
30-minute technical call · no deck