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The reliable way to evaluate an AI companion is to treat it as a data lifecycle, not a single privacy switch. Identify every data store (chats, memories, files, voice, device logs and connected services), determine each purpose and whether model training is involved, map recipients and international transfers, then test export and deletion controls against the provider’s stated retention deadlines and exceptions. A chat disappearing from your screen does not necessarily remove extracted memories, safety records, backups, de-identified data or information already incorporated into a training run.
This guide gives you a repeatable audit you can use before sharing sensitive information and whenever an app changes its features or policy.
What exactly are you evaluating when you audit an AI companion?
An AI companion can create several related records from one conversation. The visible transcript is only one layer. A service may also save a profile field, a “memory,” a diary entry, a conversation summary, an embedding used for retrieval, moderation or safety events, analytics, backups, and content sent to another model provider to generate a reply.
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- Collection: What information is captured, including identifiers, message content, uploads, voice, video, location and device signals?
- Purpose: Is it needed to provide the reply, personalize the companion, prevent abuse, measure usage, or improve models?
- Location and recipients: Which company, cloud host, language-model provider, analytics vendor, payment processor or connected app can process it?
- Retention: What starts the deletion clock, how long is the stated period, and which legal, security, backup or de-identification exceptions apply?
- Control: Can you access, export, correct, restrict, delete or opt out, and does the control cover old data or only new activity?
- Reversibility: Can information already used in a training run, aggregate, classifier or backup be removed or disconnected from you?
Record the policy’s effective or update date and the exact in-product setting name. Privacy controls change faster than a static review can keep up.
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How do I inventory every data store?
Start an inventory before judging whether a service is “private.” Read the privacy policy, help center and settings screens together; each often describes a different layer.
Chat history
Note whether conversations are stored by default, synchronized across devices, searchable, or automatically deleted. Check whether deleting one thread removes attachments and generated summaries as well as the visible messages.
Persistent memory, profile and diary
Companions may extract names, relationships, interests, health details or preferences into a profile or memory store. These records can remain after a chat is hidden. Look for a separate memory-management screen and an option to inspect, edit and delete individual entries.
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Uploads, voice and video
List every file type and recording feature. Ask whether the original file, a transcript, thumbnails, face or voice features, and moderation copies have separate retention periods. A “delete message” action may not cover an uploaded file held in another service.
Feedback and safety records
Thumbs-up or thumbs-down feedback, abuse reports and automated safety classifications can be retained for quality or security work. Determine whether they are linked to your account and whether account deletion removes them or only removes direct identifiers.
Usage, device and network data
Check for IP address, browser or device identifiers, operating-system details, crash logs, approximate location, timestamps and interaction metrics. Character.AI’s published description includes account information, interaction-generated data, usage data, IP address and data from some connected services. Replika describes profile data, messages and content, interests and preferences, payment information, device and network data, and usage data.
Connected services
If the companion can access calendars, contacts, storage, social accounts or other integrations, record the permission scope, token lifetime and revocation path. Disconnecting an integration may stop future access without deleting copies already imported.
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How can I tell whether conversations are used to train the AI?
Search the settings and policy for model improvement, training, personalization, memory and human review. Do not treat “we do not sell your data” as a statement that content is never processed by other parties or used for improvement.
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Check the default and the scope of an opt-out
Write down whether improvement is on by default, whether the switch applies to all content or only future content, and whether opting out also stops personalization, safety analysis, search or recommendations. Confirm whether the setting is available in your country, age category and plan.
OpenAI says eligible personal accounts can turn model improvement off, while business, enterprise, education and healthcare workspaces have different defaults. A managed workspace can apply retention and access rules that an individual user cannot change.
Example: a regional opt-out path
Character.AI documents an EEA and UK path: in the app, open Settings > Data & Privacy; on the web, open Settings > Account > Manage Account & Data > Model Improvement. The company says that after opting out, new content will not be used to train its generative models. The same documentation says content may still be used for search, recommendations and safety classifiers, so the switch is not a universal processing ban.
Ask what “personalization” means
Personalization can involve a profile, retrieval index, summaries or recommendation model without being called training. Ask whether your prompts are used to tune a shared model, to improve a private model for your account, or only to retrieve your own saved context. Those are different risks and have different deletion implications.
What is the difference between chat history and memory?
History is the transcript you can see; memory is information extracted for future conversations. Deleting one does not automatically prove that the other is gone.
Replika’s help documentation says users can view, edit and delete remembered details, but complete message-history deletion requires deleting the account. The same documentation says only four months of chat history is displayed while memories and diary entries remain accessible. That means a short visible history is not evidence of short overall retention.
During an audit, test these actions separately:
- Delete a single conversation and verify whether it disappears from every device.
- Open the memory, profile and diary views and look for facts extracted from that conversation.
- Ask the companion what it remembers, then compare the answer with the memory-management screen.
- Export your account and inspect whether transcripts, memories, summaries and metadata appear as separate files.
- Request deletion and ask specifically about embeddings, summaries, safety logs and backups.
If support cannot explain whether a deleted message remains in an extracted record, treat that uncertainty as a retention risk and avoid sharing information you would not want stored.
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How long does an AI companion keep my data?
Retention figures are meaningful only with their trigger, data category and exceptions attached. The following published statements cover different datasets and should not be compared as if they measured one common store.
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| Provider and source date | Published period | What the period covers | Important qualification |
|---|---|---|---|
| OpenAI (2026) | Within 30 days | Deleted personal data; Temporary Chats are automatically deleted within 30 days | Legal, safety, security, accounting and de-identification conditions can apply. De-identified or disassociated content may no longer be tied to an account. |
| Replika help documentation (2026) | Four months visible | Chat history shown in the product | Memories and diary entries can remain accessible; visible history is not the complete retention period. |
| Replika privacy policy dated March 2, 2026 | Up to 60 days after termination | Profile information, messages and content processed to perform the service | Specified account, financial, device and legal-retention categories may be kept up to 10 years. |
| Anthropic (2026) | Within 30 days | Deleted conversations removed from backend storage | If model improvement is enabled, de-identified data may remain in training pipelines for up to five years. |
When reading any policy, capture five details in your notes: the event that starts the clock, the exact category covered, the promised deadline, the exceptions, and whether the deadline applies to production systems only or also backups and derived datasets.
Can deleting a chat or account remove data already used for training?
Usually, not completely. Deletion can remove an account-linked record while leaving a derived or de-identified copy that no longer points to you.
Anthropic states that turning off model improvement does not remove data from training runs already in progress or from models already trained. Its explanation distinguishes immediate removal from chat history, backend deletion within 30 days, and possible retention of de-identified training-pipeline data for up to five years when improvement was enabled. OpenAI likewise notes that de-identified and disassociated content may no longer be tied to an account when deletion occurs.
Ask support these precise questions rather than “Is it deleted?”:
- Has this content entered a completed or running training job?
- Can you suppress it from future jobs after I opt out?
- Are summaries, embeddings, classifier outputs or analytics aggregates deleted?
- Are backups overwritten on a schedule, and can restoration reintroduce the record?
- What confirmation will I receive, and what remains under legal or safety exceptions?
Who can see or process my conversations?
Map recipients by function, not just by the company name displayed in the app. A companion may use cloud hosting, a language-model subprocessors, analytics, customer support, payment services, security vendors and connected apps.
Replika says conversation data sent to third-party language-model providers is de-identified and minimized, used to generate responses, processed transiently, and subject to contractual deletion and no-training restrictions, with security and legal exceptions. “Transient” describes the intended processing window; it does not mean your account has no other stored copy.
Check the policy for international transfers, contractual safeguards, human-access procedures and incident handling. If a provider offers a human review setting, determine whether reviewers see full conversations, selected snippets or only flagged content, and whether opting out affects safety monitoring.
Which rights and account conditions change the result?
Privacy controls depend on geography, age, subscription, and who administers the account. Character.AI lists region-dependent rights to access, correct, delete, object, restrict and obtain portability. OpenAI warns that administrators of managed workspaces and their retention policies can control what users can do.
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- Region: Record the country associated with the account; rights and opt-out eligibility can differ.
- Age: A minor account may have different consent, deletion or monitoring rules.
- Plan: Consumer and organizational plans can use different defaults and contracts.
- Administrator: Employer or school accounts may be exportable or retainable by the organization rather than the individual.
- Payment status: Closing a subscription may stop billing without closing the account or deleting content.
How do I perform a reproducible privacy and retention audit?
Use the same sequence for every companion and save evidence as you go.
- Create a test account context. Record country, age category, plan, login method and whether an administrator controls it. Do not use real medical, financial or intimate information during testing.
- Capture the policy date. Save the privacy policy, retention language and subprocessor list with their effective or update dates.
- Inventory data stores. List history, memory, diary or profile, uploads, voice and video, feedback, safety logs, device data and connected services.
- Record defaults. Screenshot or transcribe the exact labels for model improvement, personalization, memory, human review and analytics.
- Test the opt-out. Turn it off, note the confirmation, and determine whether it covers existing content, only new content, or only selected features.
- Run a deletion test. Create a harmless conversation containing a unique test phrase, delete the chat, then search history, memory, diary, exports and the companion’s recalled context.
- Request an export. Keep the downloaded files and note missing categories, formats, timestamps and whether metadata is included.
- Close or delete the account if appropriate. Record the confirmation, stated deadline and any cooling-off period during which reactivation is possible.
- Ask targeted support questions. Query training runs, embeddings, summaries, backups, safety records, processors and legal exceptions; keep the ticket number and response.
- Recheck after change events. Repeat the review after a major feature release or policy update. Character.AI’s training-settings article was updated October 30, 2025, and Replika displays a privacy policy dated March 2, 2026, illustrating why dates matter.
Store your evidence separately from the companion account. A screenshot proves what the interface showed on that date; it does not prove that backend deletion completed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can I compare two companions fairly?
Use a scorecard that keeps unlike promises separate. Give each criterion a rating such as clear, partial or unclear, and attach the supporting policy sentence or screen capture.
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|---|---|---|
| Collection scope | Messages, memory, voice, files, identifiers, device and location data | Sensitive categories create different exposure if retained or shared. |
| Improvement defaults | Whether training or model improvement is on, and opt-out eligibility | An opt-out that covers only future content leaves earlier data in scope. |
| Memory separation | Independent controls for history, profile, diary, summaries and embeddings | Deleting a transcript may not delete extracted context. |
| Deletion lifecycle | Deadline, trigger, backups, legal exceptions and de-identification | “Deleted” can mean removed from the interface, backend or account link. |
| Recipients and transfers | Processors, countries, contractual limits and human access | Processing by another provider is different from a sale but still expands exposure. |
| User and admin rights | Access, correction, portability, deletion and workspace administrator powers | Account context can override an individual’s preferred setting. |
| Control quality | Exact path, confirmation, scope and reproducibility | A clear, testable control is more useful than a broad promise. |
What are the most common evaluation mistakes?
Assuming an empty history means deletion
Check memory, diary, exports and support confirmation. A display limit or hidden archive can make a service look more ephemeral than it is.
Confusing no sale with no third-party processing
Review subprocessors and connected services. Data can be processed to generate a response or provide analytics without being sold.
Treating an opt-out as retroactive
Record whether the switch applies to new content only. Ask what happens to content already in a training queue or completed model.
Comparing retention numbers without scope
Four months of visible history, 30 days for backend deletion and five years in a de-identified training pipeline describe different stores. Put the category beside every number.
Ignoring managed accounts
An employer or school administrator may set retention, access and export rules. Test the account context before sharing sensitive material.
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Failing to save evidence
Policies and settings change. Keep dates, exact labels, screenshots and confirmation messages, then repeat the audit after major updates.
What should I do before sharing sensitive information?
Use the least identifying detail necessary, disable model improvement when available, turn off persistent memory if you do not need continuity, and avoid uploading documents that contain names, account numbers or location history. Prefer a temporary or guest mode only after confirming what “temporary” excludes; a mode that hides history may still generate safety or security records.
For work, school or clinical use, obtain the administrator’s retention terms and confirm whether the organization—not you—controls deletion and export. For any companion, assume that a message may be copied into a derived record until the provider clearly explains otherwise.
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Does an AI companion remember everything I say?
Not necessarily. It may retain a visible transcript, selected memories, diary entries, summaries or safety records, each with separate controls and lifetimes. Ask the service to show its memory store and test deletion with a harmless, unique phrase.
Can I delete my AI chat history permanently?
Only if the provider’s process covers backend storage and derived records, not just the screen. Check the stated deadline, backup and legal exceptions, and whether account deletion is required; some services say complete history deletion is unavailable without closing the account.
Are my conversations used to train the AI after I opt out?
An opt-out generally governs future use, but wording differs by service and region. Data already in a training run, a completed model, a safety classifier or a de-identified dataset may not be removable, so ask specifically about those stages.
How can I tell whether a third party receives my messages?
Read the provider and subprocessor disclosures and look for language about language-model, hosting, analytics, support and connected-service vendors. Also check whether content is minimized, processed transiently, contractually barred from training, or accessible to human reviewers.
What evidence should I keep after changing privacy settings?
Save the policy update date, exact setting label and screen path, confirmation messages, export files, deletion request number and support replies. These records establish what the service promised and showed at the time you made the change.
The Bottom Line
Judge an AI companion by its complete data lifecycle: collection, memory extraction, model-improvement use, recipients, retention exceptions and verifiable deletion. If a provider cannot distinguish chat history from memory and derived data, cannot state what an opt-out covers, or cannot explain what survives account deletion, limit what you share or choose a service with clearer controls.
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