Questions to ask an AI or software partner in regulated industries

Areusdev does not use client data to train, fine-tune, or benchmark shared models unless we agree in writing for a specific engagement. Project data stays scoped to your engagement. If a delivery uses a third-party model API, we document that subprocessor and keep your data out of vendor training by default through contract and configuration.

We map data flow per project: regions, cloud accounts, and any embedded AI services such as cloud model APIs. Subprocessors are named in the agreement. You approve sensitive processing locations before go-live when your policy requires it.

We design for industry-standard encryption in transit (TLS) and at rest (AES-256 class controls on modern cloud platforms), with key management aligned to your cloud account. Bring-your-own-key is supported when your cloud and architecture allow it.

We operate with documented incident response for delivery and managed services engagements. Notification timing and severity definitions are set in the contract (typically within regulatory and customer SLA windows). Ask us for the current process summary during security review.

For systems we build and run under managed services, SLAs, RTO/RPO, and backup/restore tests are defined per engagement. For build-only projects, we design operability into the architecture and hand runbooks to your team or your chosen operator.

On termination we follow the contract: return or delete project data in scope, including backups where technically feasible, within an agreed window. Retention required by law or your written instruction is documented separately.

Yes. Serious regulated buyers should. We support security questionnaires, architecture reviews, and reasonable third-party assessments under NDA before or during contracting.

You own your patient and clinical data. We design for portability and standard interchange (including FHIR/HL7 where the engagement requires it) so you are not locked into a proprietary dead end.

Liability is allocated in the contract. We do not position Areusdev as a clinical decision maker. Clinician oversight, validation scope, and insurance requirements are agreed before production use in care workflows.

We prefer architectures clinicians can inspect and override. Recommendations are tools for staff, not silent automation over care decisions, unless you explicitly commission a different regulated product path with the right clearances.

We support validation work and evidence gathering for products we engineer. Published studies or regulatory clearances belong to the product owner (often you). We help generate the technical evidence package the pathway requires.

For systems we maintain, we agree monitoring, revalidation triggers, and notice before material model or prompt changes that affect clinical or regulated behavior.

It is a common starting framework from the Coalition for Health AI (CHAI) for reviewing vendor AI solutions before approval. CHAI released the playbook on 1 October 2026 as a draft, and as of October 2026 it is being piloted with health systems and AI vendors. Its companion workbook sets out 57 yes or no controls across 11 domains, drawn from more than 800 questions in about 16 health system questionnaires, and applies them by deployment risk. With an engineering partner, use it as the checklist: ask which controls the partner’s work can evidence, and which stay with you or the product owner.

Engineering evidence for systems we build or integrate, mapped to the playbook’s domains. Security & Access Control: encryption design, incident response summary, pre-contract security review. Data Integrity & Lineage: data flow map, named subprocessors, and no client data in shared-model training without written agreement. Model Validation & Performance Monitoring: agreed monitoring and revalidation triggers for systems we maintain. Transparency & Traceability: model documentation, versioned models, prompts, and pipelines. System Reliability & Resilience: SLAs, RTO/RPO, runbooks. User Experience & Workflow Integration: clinician override, FHIR/HL7 interchange. Legal & Regulatory Compliance: a BAA when PHI is in scope. Clinical safety, fairness, and ROI evidence sits with the product owner; we support validation work.

No. The CHAI playbook is a draft intake framework, piloted as of October 2026, that helps a health system gather comparable evidence before it approves a vendor AI solution. It is not a law or a regulatory pathway, and CHAI says it does not replace each organization’s own judgment. Obligations under FDA rules, the EU MDR, or the EU AI Act stay with the parties those laws name, decided with your counsel. Areusdev does not classify products or give legal advice. We build and document the engineering evidence that both an intake review and a regulatory pathway rely on.

No, not without explicit written consent for a named purpose. Research IP stays in your tenancy or agreed private environment.

Yes. Many biotech engagements use VPC-isolated or private cloud patterns. Air-gapped designs are scoped when your policy demands them.

When we train or fine-tune a model for you, we document data sources in scope, intended use, metrics you approved, and known limits. When we integrate a third-party model, we require and relay the vendor model documentation.

Scientific workflows need pins. We version models, prompts, pipelines, and infra so you can reproduce runs and audit changes between releases.

When PHI is in scope we work under HIPAA-aligned controls and BAA arrangements as required by your counsel and the delivery design. Confirm BAA needs before any PHI is shared.