AI Apps tool
AI app export risk checker
Find export, deletion, ownership, and migration gaps before an AI app becomes a daily system.
What to collect
| Data types | Notes, transcripts, files, embeddings, summaries, prompts, tags, and user history. |
|---|---|
| Export format | Markdown, CSV, JSON, PDF, API, or proprietary archive. |
| Ownership transfer | What happens when a user leaves, changes team, or deletes an account. |
How to use it
| 1 | Run an export before importing important data. |
|---|---|
| 2 | Check whether exports preserve source links, timestamps, authors, and structure. |
| 3 | Test account deletion and ownership transfer with sample data. |
How to read the result
| Low risk | Structured export | Data leaves with metadata and can be re-imported elsewhere. |
|---|---|---|
| Medium risk | Partial export | Useful notes leave, but embeddings, links, or history are lost. |
| High risk | No practical export | Do not make it a system of record. |
Useful vs risky
| Healthy | The export can rebuild the workflow in another tool. |
|---|---|
| Risky | The app has great recall but no credible migration path. |
Buyer tools
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