All-in-one anonymizing AI chat vs. your own ChatGPT or Claude
An all-in-one AI chat with built-in anonymization is convenient, but it usually costs more, gives you only the raw model, and has to receive your original text first. Anonymizing locally and using your own AI keeps the full product, predictable cost, and your data on your machine.
Updated
An all-in-one AI chat with built-in anonymization is convenient, but it has three downsides: you usually pay per token, often with a markup, instead of a flat subscription you may already have; you only get the raw language model, not the full ChatGPT or Claude product; and if the anonymization runs on the provider’s server, your original text has to reach that server first. Anonymizing locally and using your own AI keeps the full product, predictable cost, and your data on your machine.
The two approaches
The built-in approach: a provider gives you their own chat interface that calls ChatGPT, Claude, or Gemini in the background and anonymizes automatically. You work inside the provider’s software.
The local approach: you remove personal data locally on your device, then use your ordinary ChatGPT or Claude. Anonymization is separate from the AI.
Downside 1: unclear and usually higher cost
With a built-in chat you typically pay per token for the underlying model, often with the provider’s markup on top. The cost is hard to predict and grows with the length of your documents, and long documents are the typical use case. A flat monthly plan for ChatGPT or Claude, which many people already have, is usually more predictable and often cheaper for regular use.
Downside 2: the model, not the product
A built-in chat generally only has access to the underlying language model. The software around it, which gives the real apps their value, is missing: projects, web search, file and document tools, artifacts, memory, extensions, mobile apps, and agentic features. You also depend on the provider’s implementation, which tends to lag behind new models and features.
Downside 3: your raw data reaches the server first
For a hosted service to anonymize your text, it first has to receive it. If that anonymization runs on the provider’s server, your sensitive data leaves your device and reaches that server before it is removed. With a local tool, anonymization happens before anything leaves the device, and you can verify this from the network traffic.
Further points
- New models arrive later: when a new ChatGPT or Claude ships, the real apps have it immediately. A built-in chat integrates it later, if at all.
- Less control: automatic background anonymization skips the review step, so a missed item goes straight to the model. With the local flow, you confirm every detection before anything is sent.
- No lock-in: your history and way of working stay in your own AI, not in someone else’s software.
- Not just chat: local anonymization works with any tool and any future model, not only a chat interface.
The honest trade-off
The built-in chat is more convenient, because there is no copy-and-paste. That is the real advantage. The question is whether that convenience is worth giving up your subscription, the full product, keeping data on your device, and your own control.
At a glance
| Criterion | Built-in AI chat | Anonymize locally + your own AI (Stript) |
|---|---|---|
| Cost | Per token, often with a markup | Your existing flat subscription |
| Scope | The raw model only | The full ChatGPT or Claude app |
| New models | When the provider integrates them | Immediately, in the real app |
| Your raw data | Reaches the server if anonymization is server-side | Never leaves your device |
| Review before sending | Automatic, limited | You confirm every detection |
| Works with | That chat only | Any tool, any model |
Keep your AI, your cost, and your data under your control. Download Stript for free →