Choose local or cloud AI for recorded work

Choose between local and cloud AI providers for Screenpipe, and understand what transcription, AI requests, sync, and connected apps send off your device.

Choose the AI provider separately from your recording and storage settings. Local capture does not mean every AI request stays local. Cloud transcription, cloud AI, media analysis, sync, and connected apps each create their own data path.

Screenpipe plans and AI subscriptions

Where you ask	What access it uses
Screenpipe chat with the Screenpipe provider	Your Screenpipe account and its available AI allowance; inspect usage and controls
Screenpipe chat with ChatGPT	The supported ChatGPT sign-in flow and that account’s limits
Screenpipe chat with Claude API	An Anthropic API key and API billing, separate from Claude Pro/Max
Claude Desktop or Claude Code connected through MCP	Your access to that Claude client; Screenpipe supplies local recordings through MCP
Screenpipe chat with Ollama	A local Ollama server and a model that supports the required tools
Another API provider	That provider’s supported endpoint, credentials, billing, and limits

A Screenpipe subscription does not include a separate Claude Pro/Max or ChatGPT subscription. A provider subscription does not replace a Screenpipe app license. Selecting a Claude model offered by a Screenpipe plan is different from owning a Claude subscription.

For Day Recap, first verify that the selected provider can answer one small question about recent recordings. Then run the recap for a day that has captured data. Check its dates and source evidence before relying on the summary. See your first useful result.

Start here

List the inputs needed for one task: text, audio transcript, images, or an external app. Inspect the selected transcription provider and the model used by that task. Review enabled sync and media-analysis settings before testing.

Copy this prompt

Use this in Screenpipe chat or an assistant with the required connections. Replace the brackets with your details. If the assistant lacks access, provide a reviewed excerpt; a prompt alone does not connect it to your history.

Help me compare two configurations for [task]: [configuration A] and
[configuration B]. Use only settings or documentation I provide.
For capture, transcription, AI inference, media analysis, sync, and external
writes, list input, destination, purpose, and any unknowns.
Compare a small reviewed sample for accuracy, latency, and observed usage.
Do not claim that a local database makes the entire workflow local.

Check the result

Run the same bounded task with the chosen configuration and inspect the answer against its sources. A faster answer is not useful if names, decisions, or source times are wrong.

See a worked example

Decision	What to verify
Local model	It supports the task and has enough machine resources.
Cloud model	Which context is sent and which provider processes it.
Transcription	Whether audio processing is local or uses a service.
Connected app	What request or output reaches that external system.

Go deeper: setup choices and edge cases

Local models can reduce reliance on a remote inference service, but their quality, context capacity, and resource demands vary. A small text summary and a long multimodal investigation are different workloads.

Avoid assuming one provider selection controls every scheduled task or integration. Check the task configuration and failure behavior. If a fallback provider is configured, include it in the data-flow review. Use actual account usage for cost comparisons rather than converting a single run into an unlimited-use promise.

Continue

Ollama · privacy data flow · AI usage and controls