SideNote Pro

Is a BYOK AI assistant private?

Bringing your own key removes one party from the path. It does not make an AI assistant private on its own, and anyone telling you otherwise is selling something. Here is the actual architecture, so you can judge it yourself.

What BYOK actually changes

In a bundled AI product, your prompt goes to the vendor's server, which then calls a model provider. Two organisations see your data, and you have a relationship with only one of them.

With BYOK, your prompt goes from your machine to your provider. One organisation sees it, and it is one you chose and have terms with. That is a real improvement, and it is a smaller one than *private* implies.

BYOK is not automatically more private. It removes an intermediary. Your provider still receives everything you send, under its own retention and training policies. If you have not read those policies, you have not gained privacy, you have changed who holds the data.

What stays on your machine

Everything SideNote Pro persists lives under %LOCALAPPDATA%\SideNote Pro\, with no cloud copy of any of it.

Local data and its protection
DataProtection
Application and provider settingsPlain local JSON
Provider API credentialsWindows DPAPI, current user, in separate files
Conversation archivePlain JSON by default, optionally DPAPI
Local folder indexesWindows DPAPI, current user
Usage ledgerPlain local JSON, aggregates only
Trial and licence stateWindows DPAPI, current user

API keys are never written into settings.json. Folder indexing, extraction, search and ranking are entirely local, with no network call. The usage ledger holds counts, dates, provider and model provenance and cost aggregates, never prompts, responses, filenames, document contents or image data.

What leaves the machine, and when

When you press Send, and only then, a request goes to the provider you configured. Depending on what you attached, it can carry:

  • your prompt, and the system prompt from Settings;
  • recent conversation context, and the compaction summary when one exists;
  • text captured by a selected-text action;
  • text extracted locally from attached documents;
  • image data from attachments and screenshots;
  • the folder excerpts local retrieval selected.

One additional provider call is worth knowing about: context compaction asks your model to summarize older messages when a thread outgrows its budget. It is still your provider and your key, and it means older conversation content is sent to the model to be summarised.

What SideNote Pro never does

  • No telemetry or product analytics.
  • No user account, and no advertising.
  • No cloud conversation storage and no cross-device sync.
  • No background screen capture, microphone listening, camera access or clipboard polling.
  • No automatic file or folder discovery, and no background filesystem watcher.
  • No embeddings and no vector database, so your corpus is never sent to an embedding service.
  • No queries against your provider's billing system.

Screenshots, clipboard images and selected text are read only after an explicit action: starting a capture, pressing Ctrl+V, or invoking an action shortcut.

What BediniLabs receives

The licensing service answers one question: is this installation entitled to run. It handles trial authorization, activation, entitlement refresh and device deactivation, and stores licensing and device metadata to do so.

It does not receive prompts, responses, attachments, screenshots, filenames, folder contents, usage figures or your provider API key. Your AI requests do not pass through it, and it is not a proxy for your provider. Activation keys are sent when you activate and are not persisted locally afterwards.

The full policy is on the privacy page.

If you need content never to leave the machine

Configure a local provider. With Ollama or LM Studio, the request goes to localhost and inference runs on your hardware. This is the only configuration where *nothing leaves the machine* is literally true.

Two honest caveats. SideNote Pro does not supply the local model and cannot guarantee the behaviour of third-party software; what it controls is the destination of the request. And local models are generally less capable than the best hosted ones, so this is a real tradeoff rather than a free upgrade.

The practical pattern most people land on is two profiles: hosted for ordinary work, local for anything confidential, switched from the composer. See using local models for private workflows.

A checklist for evaluating this yourself

  1. Read your provider's data retention and training policy. This is the largest factor and it is entirely outside SideNote Pro's control.
  2. Check whether your provider offers a zero-retention or enterprise tier if your work requires one.
  3. Decide which categories of content you are willing to send to a hosted provider at all.
  4. Configure a local provider for the categories that fail that test.
  5. Turn on conversation history encryption if the machine is shared or portable.
  6. Set a retention period so old threads do not accumulate indefinitely.
  7. Check the composer's profile picker before sending anything sensitive.

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