Isolation is physical first, fails closed everywhere else, and is enforced in the build. This page answers the questions your security, compliance and AI governance teams ask first, in plain language and without the runaround.
Every customer runs in its own dedicated cloud environment with its own network, machine, key vault and backups. The shared management plane holds no customer data beyond privacy-safe telemetry.
Credentials live only in your key vault. Four separate layers keep keys and secrets out of what the model sees and what it says, and the AI never holds the keys that route its own model calls.
Data is encrypted in transit and at rest. On regulated deployments every memory entry is encrypted, including its search index, with keys derived per agent.
Every decision leaves a chained, privacy-safe receipt, verified when stored and again on every read, alongside an audit record of the actions the AI takes.
Daily backups, immutable time-locked copies the AI itself cannot touch, and offsite copies in a separate region. Restores are verified automatically every week.
Consequential actions are held for the right person to approve. Authority comes only from verified identity and recorded grants, never from a title typed in a profile.
If code in one customer's environment ever asked for another customer's data, it would fail with an alarm rather than return anything. An unknown setting is treated as the most protected one.
Built and operated on US-region cloud infrastructure, with a region allowlist checked automatically.
Every release carries signed build provenance, is scanned before deploy, and reaches regulated customers only after it is proven on internal agents first.
The short version: your data is yours, it stays isolated, it is used only to do the work you direct, and it never trains our models.
Security covers the data. Governance covers the decisions. ANDR3W was built so both can be verified, not just asserted.
How accountability worksWe say "aligned" and "supports" deliberately. None of these is a certification, and we will never present one as if it were.
Governance, measurement and monitoring are built into the platform: checks with measured accuracy, receipts for every decision, and alerts on any residual risk.
Model auditability, audit logging, data lineage and post-deployment monitoring are things we can show you, not just describe.
Receipts, outcome records and monitoring give your AI governance committee the evidence it needs to oversee the tools you use.
A model card covering intended use, out-of-scope uses, data handling and known limits, shared during security review.
We take compliance seriously enough to be precise about it. Here is where we are and where we are headed. No overstatement, because your risk team will check.
We use a short, vetted set of enterprise infrastructure and AI-model providers to deliver the service, each under appropriate data-protection terms and, where applicable, a Business Associate Agreement. We maintain a current subprocessor list and provide notice of changes as set out in your agreement.
We monitor continuously and maintain a defined process for detecting, investigating, and responding to security events, including timely notification consistent with your agreement and applicable law. Our providers are contractually obligated to notify us of security incidents so we can act quickly.
We are glad to walk your security, compliance, and IT stakeholders through our architecture and controls in detail, and to complete your vendor security review.