Service
Secure & Compliant AI Deployment
Run AI on sensitive data without it leaking or training a public model — from enterprise APIs with no-training guarantees to fully self-hosted models, matched to your actual regulatory exposure.
Secure AI deployment means running AI so sensitive data never trains a third party’s model, is never retained beyond processing, and never leaves a boundary you control — with access control and audit trails. We engineer the right tier for your exposure: enterprise API with no-training guarantees, private VPC deployment, or fully self-hosted open-weight models.
The problem
The deployment spectrum — and where each breaks
There are four real tiers. Public consumer tools (chatgpt.com) are off the table for regulated data — a US court found documents run through a free LLM lost attorney-client privilege. Enterprise APIs (Azure OpenAI, AWS Bedrock, Google Vertex) contractually don’t train on your data, isolate it per-customer, and carry BAAs/DPAs — this is where most regulated workloads correctly land. VPC/private-networking adds PrivateLink/Private Endpoints and customer-managed keys on top. Fully self-hosted open-weight models (Llama, Mistral, Qwen) on your own GPUs are maximum sovereignty — the only tier where no third party ever sees a token.
The nuance that separates real expertise from "we keep your data safe": the enterprise-API tier is genuinely compliant for most regulated workloads. Self-hosting is more sovereign, not automatically "more compliant" — and it carries real cost. We match the tier to your exposure and threat model.
The solution
Where automation removes the friction
Compliance, precisely
We map deployment to the frameworks that bind you. HIPAA needs a signed BAA — but coverage is configuration-dependent: with some providers a single call made without HIPAA/zero-data-retention mode enabled falls outside the BAA even when one is signed. SOC 2 Type II is what enterprise buyers actually require, and every sub-processor is a new boundary. GDPR distinguishes data residency (where data sits) from sovereignty (whose law governs it — the US CLOUD Act reaches hyperscalers regardless of region). For finance, there’s no AI-specific SEC/FINRA rule — the binding obligation is recordkeeping (Exchange Act 17a-4, FINRA 4511): prompt/output logging, version tracking, access controls. The EU AI Act’s high-risk timeline is shifting, so we treat any extension as contingency, not baseline.
The architecture
Customer-managed keys in your KMS/HSM (not provider defaults); RBAC + SSO with per-user and per-service identity; audit logging that captures who/what/when while keeping sensitive payloads out of the logs; PII/PHI detect-and-redact (e.g. Presidio + tokenisation); guardrails for prompt-injection and output safety; and pinned data residency. The dominant pattern is RAG into your approved internal source-of-truth so the model cites your data rather than relying on parametric memory.
When self-hosting is worth it
Self-hosting only wins on cost at sustained high volume — raw GPU is just 30–40% of true cost; MLOps, on-call and security patching are the rest. We run open-weight models on vLLM with right-sized GPUs (e.g. ~2× A100/H100 for a 70B model), but we’ll tell you when an enterprise API is the smarter call. A well-served open model with good RAG context closes most of the quality gap.
Example workflows we build
- Enterprise-API deployment with no-training & BAA configuration
- VPC / private-endpoint networking with customer-managed keys
- Self-hosted open-weight models on vLLM (right-sized GPUs)
- RBAC + SSO, PII/PHI redaction, and audit logging
- Compliance mapping (HIPAA, SOC 2, GDPR, SEC/FINRA)
The results
The commercial impact
Our approach
From manual to automated
- 01Map exposure & threat model
Your data sensitivity, regulatory obligations (HIPAA/SOC 2/GDPR/SEC-FINRA), and the deployment tier that fits.
- 02Architect the deployment
Enterprise API, VPC, or self-hosted — with KMS, RBAC/SSO, audit logging, PII redaction and guardrails.
- 03Verify compliance controls
BAA/DPA configuration, residency, recordkeeping and audit trails validated against your obligations.
- 04Deploy & monitor
Go live in your boundary with observability, drift monitoring, and retention controls.
Why a custom build beats off-the-shelf
- We match the least-isolated tier that satisfies your exposure — no over-engineering.
- Compliance treated precisely (BAA config, residency vs sovereignty, recordkeeping), not hand-waved.
- Customer-managed keys, RBAC, redaction and metadata-only audit logging.
- Honest on self-hosting cost — we recommend an enterprise API when it’s the smarter call.
Frequently asked questions
Is it safe to use AI with regulated data like PHI or MNPI?
Yes, with the right tier — never on public consumer tools. Enterprise APIs with no-training guarantees and a BAA cover most regulated workloads; for maximum sovereignty we self-host open models in your environment so no third party ever sees a token.
Do we need a self-hosted model to be compliant?
Usually not. Enterprise APIs (Azure OpenAI, Bedrock, Vertex) are genuinely compliant for most workloads with the right configuration. Self-hosting is more sovereign, not automatically more compliant — we recommend it only when your exposure or volume justifies the cost.
Does Azure OpenAI / Bedrock / Vertex train on our data?
No — their enterprise tiers contractually don’t train on your data and isolate it per customer. The nuance is configuration: features like HIPAA mode or zero-data-retention often must be explicitly enabled, and a single mis-configured call can fall outside your BAA.
What’s the difference between data residency and data sovereignty?
Residency is where the data physically sits; sovereignty is whose laws govern it. A hyperscaler can pin your region (residency) but the US CLOUD Act still reaches it (sovereignty). True sovereignty means provider, infrastructure and operations in one jurisdiction — which can require self-hosting.
How do you keep an audit trail without leaking sensitive data into logs?
We log metadata — who, what, when, model version, status — and keep sensitive payloads out of the logs, with PII redaction, RBAC, and retention set to your obligations (e.g. HIPAA’s 7-year requirement).
What does it cost?
Engagements are fixed-price and scoped to the outcome. Every engagement is fixed-price with ROI targets agreed up front, backed by our 90-day ROI guarantee. Book a free audit for a clear price and ROI estimate.