Security and data handling
How Middleout accesses your sources, where it runs, which models it uses and how it keeps each organization separate.
Read-only
Middleout never modifies your data.
- BigQuery: read-only permission (
bigquery.readonly), or read roles you give your organization's service account from your own IAM. - Google Sheets and Drive: read-only permission (
drive.readonly), or shared read access with your organization's account. - SQL databases: each query runs in a read-only transaction.
Limits per query
So that a question does not read more than it should:
- Each query has a cap on the data it reads, enforced by BigQuery itself.
- A query returns up to 10,000 rows; a dashboard chart, up to 1,000; an export, up to 50,000.
Separation between organizations
Every piece of data belongs to an organization. A query without a defined organization fails instead of returning rows, and the work Middleout does with nobody present uses only the organization's sources, never personal ones.
Within an organization, each person sees only what their permissions allow. An assistant connected over MCP sees exactly the same as the person who connected it.
Credentials
- With the BigQuery service account, Middleout stores no key: access is granted and removed from your IAM.
- Authorizations with Google or GitHub can be revoked at any time from your account in those services.
- Assistants connected over MCP use OAuth with temporary access that renews itself. They never receive your password, and you disconnect them from Settings → Connected assistants.
Where it runs
Middleout runs on Google Cloud (Cloud Run and Cloud SQL), in the us-east1 region (United States).
AI models
Middleout uses Gemini models through Google Cloud's Vertex AI, with Vertex AI's global location. The models are used to converse, to understand your sources and meetings, and to search by meaning.
Personal data
The processing of personal data on the Middleout site is described in the privacy policy.