Before entering sensitive data into an AI model aggregator, establish every party that may receive it, whether prompts or outputs can be logged or used for training, how long each recipient retains them, and whether you can restrict routing. An aggregator’s privacy promises do not automatically govern the model provider or connected tools that handle a request. If you cannot verify a control that matters, do not submit the sensitive material; redact it or use synthetic data instead.
Start by tracing where the data will go
An AI model aggregator gives users access to models through a common interface or API. A prompt may pass through the aggregator to a selected model provider, and a request that uses an external tool or plugin may introduce another recipient. Automatic routing can also affect which provider receives a request. Treat each party in that path as a separate data handler whose practices need checking.
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Before sending anything, identify the exact product, model, endpoint, and enabled features. Check whether the provider is selected manually or by automatic routing, and whether the request can be redirected if a model is unavailable. If a tool, plugin, or other connected service will process the prompt or its attachments, include it in the recipient list.
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- Model provider: Does the selected provider log inputs or outputs, retain them, or use them for training, evaluation, or improvement?
- Connected tools: Does a search, code, or other external feature transmit some or all of the request to another service?
- Routing: Can the actual recipient change by model choice, fallback, account setting, or request-level setting?
Do not treat a single privacy-policy statement from the aggregator as an answer about every downstream provider. OpenRouter, for example, says it does not use inputs or outputs for its own model training, while also explaining that requests are transmitted to model providers whose data practices differ. Some providers may use inputs or outputs for training or improvement. See the OpenRouter Privacy Policy and its provider-logging documentation for that vendor-specific distinction.
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Check training use separately from logging
“Not used for training” does not necessarily mean “not stored,” and “not logged” does not necessarily mean “never used to improve a service.” Ask about prompts and outputs separately, and distinguish the aggregator’s own practices from those of the model provider and any tool receiving the data.
Look for whether data can be used to train or fine-tune models, evaluate their performance, improve products, or develop safety systems. Then determine whether any opt-out exists, whether it is active by default, and whether it applies to all recipients and request types. A setting that covers the aggregator may not control a provider’s independent use of the same request.
OpenRouter’s documentation illustrates why the provider-level check matters: its own no-training statement does not establish that every provider on its service follows the same rule. Confirm the policy for the specific model and route you intend to use rather than generalizing from the aggregator’s policy.
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Find out what is logged, retained, and deleted
Retention is not one setting. A service may handle ordinary prompts, outputs, uploaded files, operational metadata, and temporary processing storage differently. The endpoint may also retain data for security, abuse monitoring, billing, legal compliance, or other operational reasons. Check the applicable terms and endpoint documentation for each category and purpose.
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Prompts, outputs, and metadata
Determine whether prompt logging is off by default, opt-in, or configurable, and whether controls differ between individual and organization accounts. Check whether responses and metadata are retained even when prompt storage is disabled. Ask how long each category remains available and what purposes justify retention.
Files and temporary processing
Do not assume an uploaded document follows the same lifecycle as text in a prompt. Check whether files persist separately, how to delete them, and whether deletion covers active systems, backups, caches, and replicated copies. Also ask whether temporary processing storage has a stated duration or deletion trigger.
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Deletion across recipients
Ask whether deleting a conversation or file sends a deletion request to downstream providers, and what the provider’s terms say about its own retained copies. Distinguish deletion from a user-visible history from deletion in backups or operational systems. If a service does not explain these boundaries, do not treat a delete button as proof that every copy has been erased.
Deletion is worth checking as a separate commitment, not just as the final step in a retention policy. Find out whether it applies to data held by the aggregator, the model provider, and any connected tool; whether it covers files as well as prompts; and whether backups, caches, or replicated copies are included. The sources reviewed do not establish one universal deletion period or a universal downstream-deletion guarantee, so look for the specific terms that apply to your chosen route.
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Use routing controls to narrow exposure
Provider allowlists, data-policy filters, or per-request restrictions can reduce the set of providers eligible to receive sensitive information. Check the exact setting, the data policy it enforces, and whether it applies to the entire account or only a particular request. Verify whether fallback behavior can send data to a provider outside the intended set.
OpenRouter documents account-level and individual-request filtering based on provider data policies. Its documentation is a concrete example of a control to look for, not evidence that all aggregators offer equivalent restrictions. If the interface exposes a filter, confirm its scope and effect in the relevant documentation before relying on it.
For any aggregator, make sure a restriction covers the route actually used—not just the preferred model—and determine whether free and paid routes or different endpoint types have different settings. If the product cannot guarantee the allowed recipient set, avoid sending material whose confidentiality depends on that restriction.
A useful test is to compare the route you intend to use with the route the setting actually permits. Check whether the control filters by provider data policy, whether it is enforced on each individual request when needed, and what happens if the chosen provider is unavailable. Do not infer that a model choice alone is a provider allowlist: routing and fallback behavior can change who receives the input.
Review contracts and regional processing for work data
For workplace, customer, or regulated information, product settings are only part of the decision. Review the applicable data-processing agreement, subprocessor terms, confidentiality commitments, and contractual promises about use, retention, security, and deletion. Confirm that the agreement applies to the particular plan, endpoint, model, and feature in your workflow.
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Regional processing claims also need precise scope. Check which data is processed in-region, whether the commitment covers prompts, files, outputs, and connected tools, and whether the selected plan and endpoint qualify. A regional hostname or a statement about routing is not by itself proof that every part of a workflow or every downstream provider is covered.
OpenRouter documents EU and US in-region routing through regional hostnames for Business and Enterprise plans. Confirm that the plan, model, endpoint, and feature you use are within that documented scope; do not infer a universal regional-processing guarantee from the example. For jurisdiction-specific compliance questions, consult your organization’s privacy team or counsel.
For a business review, compare the written commitments against the actual workflow rather than relying on a general product description. Confirm which entity is covered by the agreement, which subprocessors may receive data, and whether the terms apply to the service tier and features employees will use. If regional location is a requirement, establish whether the promise covers the precise request path and any downstream processing; escalate jurisdiction-specific questions to counsel or the organization’s privacy team.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare the controls before choosing a route
Use the same questions for each aggregator, provider, and route under consideration. A short comparison can reveal that one option has a clear provider restriction while another has a retention or contract detail that remains unclear. The comparison is a screening aid, not a security audit or legal conclusion.
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|---|---|
| Recipients | Which aggregator, model provider, or connected tool can receive the input? Can automatic routing change the recipient? |
| Training and improvement | Can the aggregator or provider use prompts or outputs for training, evaluation, or product improvement? Is an opt-out available and active? |
| Logging and retention | Are prompts, outputs, metadata, or files stored, for how long, and for which operational, safety, billing, or legal purposes? |
| Deletion | Can users delete data, and do the stated commitments cover downstream providers, backups, caches, and replicated copies? |
| Routing controls | Can the account or individual request restrict providers according to data-use or retention policy? |
| Contract and location | Are the DPA, confidentiality, subprocessor, and regional-processing commitments suitable for this use case? |
Record the answer, its source, and any uncertainty for each axis. A provider’s policy page, aggregator documentation, contract, and account setting may describe different parts of the request path. If they appear inconsistent, or if a material answer is missing, resolve that discrepancy before submitting the sensitive content.
A practical pre-submission checklist
- Classify the content. Identify personal, confidential, regulated, credential, customer, or proprietary information in the prompt and attachments. Apply your organization’s rules for that category.
- Map the recipients. Name the aggregator, the exact model provider or route, and every external tool or plugin involved. Determine whether automatic routing or fallback can change the recipient.
- Verify training and improvement settings. Check the aggregator and downstream provider separately for training, evaluation, or product-improvement use. Confirm that any opt-out exists, is enabled, and applies to this request.
- Check logging and retention by data type. Review prompts, outputs, metadata, uploaded files, and temporary processing separately. Note purposes, periods, and any operational or legal exceptions.
- Test deletion scope on paper. Find out whether deletion reaches downstream providers and what is stated about backups, caches, and replicated copies.
- Constrain routing where possible. Use documented provider filters or allowlists, and verify request scope, fallback behavior, endpoint, and plan.
- Check organizational commitments. For work or regulated content, confirm the relevant agreement, subprocessors, confidentiality terms, and regional-processing scope with the responsible privacy or legal team.
- Withhold anything unresolved. If a material control is unclear, replace identifying details with placeholders or use a synthetic example; do not send the original sensitive data.
What to do when a control is unclear
Use the least revealing input that can accomplish the task. Remove names, account numbers, credentials, unique identifiers, and unnecessary excerpts. Where practical, replace real records with synthetic examples that preserve the structure of the problem without exposing real people or business information.
If the task requires the original data, pause and ask the organization’s privacy, security, or legal contact to approve the specific service and route. A provider’s marketing description is not a substitute for a clear answer about retention, downstream use, or contractual coverage.
The Federal Trade Commission’s Office of Technology identifies sensitive and confidential business information as a salient risk when customers use model-as-a-service companies. Its January 2024 guidance says companies must honor data-use commitments and warns that using or retaining consumer data for other purposes without clear, conspicuous notice and affirmative express consent can create legal risk. The FTC states, “There is no AI exemption from the laws on the books.” Read its January 2024 privacy and confidentiality guidance. This is U.S. regulator guidance, not a legal determination for every jurisdiction or data category.
Frequently Asked Questions
Does an aggregator’s no-training promise mean my prompt will not be retained?
No. Training and logging are separate checks. An aggregator may say it does not use inputs or outputs for its own model training while prompts or files are retained for processing or other stated purposes, and the downstream model provider may have different practices. Check each recipient and feature separately.
Will deleting a prompt or uploaded file remove it from every provider?
Do not assume so. Check whether deletion reaches downstream providers and whether the commitment covers backups, caches, and replicated copies. A user-visible deletion control alone does not establish that every copy has been erased.
Can I rely on regional routing to keep every part of a request in one region?
Not without confirming its scope. OpenRouter documents EU and US in-region routing through regional hostnames for Business and Enterprise plans, but the applicable plan, model, endpoint, feature, and downstream workflow still need checking.
The Bottom Line
Before submitting sensitive data, verify the complete recipient path, training and logging practices, retention and deletion for each data type, routing restrictions, and any contract or regional commitments that apply to your exact plan and endpoint. If a material control is unclear, withhold the original and use a redacted or synthetic example instead.
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