Custom Data Preparation Pipelines

For complex integrations, we support a pipeline pattern with S3 as the handover point.

Hosting model

• Either the customer uses their own S3 bucket
• Or MeinGPT can host an S3 bucket on request

Typical workflow

1. Data is extracted from third-party systems (e.g., DMS, ERP, CRM, or domain tools)
2. A script or flow prepares the content (e.g., into document-ready formats)
3. Prepared documents are written into the S3 bucket
4. MeinGPT ingests the bucket and exposes the content through RAG

For extraction and preparation, no-code flows such as n8n can be used.

Security

Transfer and storage can be implemented with encryption (e.g., SSE-C or comparable customer-managed encryption), depending on security requirements.

Related docs

• Data Sources & RAG: how MeinGPT ingests the S3 bucket and exposes it through RAG
• Building MCP Tooling: implement your own extraction/preparation logic as an MCP server instead of an n8n flow