AI Medical Writing Software Security: Buyer Checklist

Use this checklist when regulatory, security, quality, and procurement teams qualify an AI writing workflow. Assyro publishes it as an original buyer resource. These are suggested evidence and negotiation questions; your accountable teams determine the requirements for your data and intended use.

Start with the permitted data and workflow

Name the product, proposed configuration, source types, user groups, and intended output. Distinguish a synthetic pilot from processing confidential source reports or patient-level data. Approval for one data class does not automatically authorize another.

List every processing step: upload, document conversion or OCR, retrieval indexing, model request, generated output, human review, support, monitoring, and export. Ask which company performs each step and where relevant information persists. Include optional connectors only if they are part of the proposed use.

Choose Pass, Fail, Unknown, or Not applicable for each evidence item. Record the source, revision, checked date, scope, reviewer, and required follow-up. Not applicable needs an approved reason. A missing answer stays Unknown, even when other controls look strong.

Pair these security questions with the AI medical-writing pilot plan; secure handling alone does not establish acceptable writing output.

Security due diligence checklist

The table describes evidence to obtain, not a claim that every criterion is a universal legal obligation. Agree acceptance conditions before reviewing supplier responses.

Separate subchecks when their results differ. A supplier can identify its primary storage region while leaving support access or backup regions unanswered. Mark the known part accurately and keep the remaining mandatory scope open.

Read retention statements at the right level

No training, no provider retention, and application deletion

These answer different questions. No training concerns a permitted use of data. Provider retention concerns what a particular processing service keeps under a particular arrangement. Application retention concerns the files and records the writing product stores so users can continue their work.

For a concrete example, Weave Bio's published security overview describes a zero-data-retention arrangement with its model provider while separately describing rolling backups and deletion of customer content after contract termination. The same page says Weave and its vendors do not use user data for machine learning. Those statements should be read at their stated layers; they are not a claim that the entire application keeps no data. Weave Bio data security and privacy

Ask whether document extraction, embeddings, generated drafts, diagnostic logs, and support attachments follow the same terms. Do not infer a prohibited use from silence, but do not mark an unanswered use restriction as satisfied either. Request the applicable evidence and record its coverage.

Residency, processing, and human access

“Hosted in the US” may describe one storage layer. It does not answer where an extraction service processes the file, where a fallback model runs, or where support personnel can access it. Build the geographic map from the actual configured workflow.

Determine whether your requirement concerns storage, processing, remote access, or all three. If a region is mandatory, define how the supplier handles service degradation without routing data somewhere else. A documented refusal or delayed job may fit your requirement better than an undisclosed fallback; the accepted behavior should be explicit.

Assurance evidence and practical checks

Read an assessment's named entity, service boundary, period, and relevant exceptions. Request the information your reviewers need through the supplier's appropriate confidential process. An assurance report can inform qualification; it does not substitute for checking an unaddressed workflow or prove that your configuration meets every requirement.

Use synthetic documents and authorized test accounts for practical isolation and deletion exercises. Such tests can reveal a failure in the observed path. A small successful exercise cannot establish that no exposure is possible anywhere in the system.

NIST's July 2024 Generative AI Profile provides a broader, voluntary framework for third-party dependencies and decommissioning risks. Its Appendix A.1.3 and GOVERN 1.7 considerations support asking about the full chain, including retention and downstream dependencies. This article's checklist is an editorial application of those ideas. NIST AI 600-1

Contract questions: data rights, model changes, and exit

Give procurement and counsel the evidence record, not just a list of preferred clauses. The aim is to make the purchased service and its documented operation agree. The following are negotiation questions for review in context, not ready-to-sign legal language.

Define the covered data. Does “customer data” include uploaded source material, prompts, generated text, review comments, extracted text, embeddings, and support copies? Which permissions allow the supplier to process it, and which uses require separate authorization? Identify how feedback or derived data is treated so an apparently narrow definition does not leave the main concern unanswered.

Bind commitments to the processing chain. Which restrictions apply to the software supplier and which apply to its providers? Ask how new subprocessors, optional features, and fallback routes are disclosed and evaluated. Record the process available if a proposed change conflicts with an agreed location or data-use requirement. Do not assume that the model provider's general website terms are the terms of your supplier's specific arrangement.

Make model changes reviewable. Ask what counts as a material change: a new model version, extraction service, retrieval approach, prompt configuration, or document-processing route. Request the relevant notice and evaluation evidence, including the options if your workflow cannot accept the change immediately. A promise to keep one model forever may be impractical when a provider retires it; agree the transition and containment process instead.

Reconcile deletion with retention. Specify the trigger, data classes, active-system timing, backup handling, permitted exceptions, and evidence of completion. For context, Assyro's published privacy policy describes a default customer-content retention period extending 90 days after termination or expiry unless a customer agreement states otherwise, with constraints on earlier deletion and possible backup persistence. That is a starting point for discussing the applicable agreement, not a promise of immediate erasure or continued interactive access. Assyro privacy policy, Retention

Sequence export and termination. Decide when the customer receives source files, outputs, and required review evidence; who confirms readability; and when access ends. Price any assistance or retained access separately. Retaining data for a transition window does not necessarily mean an authorized user can keep using the product throughout it.

Resolve conflicts in writing. If a proposal promises deletion of every copy within seven days but the supplied backup schedule keeps recoverable content for thirty days, do not choose whichever statement is more convenient. Identify the exact conflicting scopes and ask the supplier and counsel to reconcile the operative terms and technical process. If your mandatory requirement cannot be met, record the failure or revise the requirement through its accountable owner. A salesperson's reassurance should not silently override the evidence.

Before ending access, use the AI writing migration checklist to test whether required drafts and review records remain retrievable.

Record unanswered security requirements in the AI writing RFP workbook so they remain visible in the purchasing decision.

Completed example: a polished response still leaves a blocker

The following packet is fictional. It demonstrates how to evaluate evidence without implying a result for Assyro, Weave Bio, or another product.

Sponsor LARCH plans a synthetic-only writing pilot. Its approved criteria require named processing parties, no training use of pilot content by those parties, and a documented deletion schedule. Production qualification additionally requires documented processing and support-access countries. A separate proposed production agreement requires deletion of all recoverable customer-content copies within seven days after termination. Production data is not authorized while those requirements remain unresolved.

The supplier provides MAP-01 listing its host, extraction service, model provider, and support function. TERMS-02 prohibits training use by those named parties for the specified pilot configuration. RET-03 describes thirty-day recoverable backups after termination. The sales proposal promises seven-day deletion of every copy. A question about support-access countries is unanswered.

Do not average these rows into a passing percentage. The unanswered mandatory location question remains open, and the deletion conflict remains a failure for the stated production requirement. A synthetic pilot's narrow permission does not establish permission to upload confidential production reports.

If the vendor supplies a revised retention procedure, identify whether it actually changes the recoverable-backup period or merely changes the wording of the proposal. Request appropriate evidence for the revised process. If the buyer instead accepts a longer period, document that as a changed requirement with accountable approval; do not describe the original seven-day condition as having passed.

Other checklist rows remain unassessed in this miniature example. No claim about encryption, isolation, incident response, or assurance follows from MAP-01 or TERMS-02 alone.

Use unresolved evidence to guide the next conversation

Send each supplier the same scoped questions and ask for dated answers tied to the offered service. Assign every required unknown or failure an owner and a closure condition. Revisit the record when data classes, features, providers, locations, or contractual terms change.

For an Assyro evaluation, bring the proposed document types, processing constraints, and unresolved evidence requests. Confirm the applicable product and agreement before qualification. The useful outcome is a defensible decision about a particular workflow, supported by evidence your regulatory, security, and procurement teams can inspect.

For a proposed Assyro configuration, review the document-management offering and request evidence for the specific storage and access responsibilities in scope.