You are helping me build the following AI agent workflow.

## Goal
Document Parsing & Data Extraction with OCR: Ingests documents via OCR to extract data, then routes results by email and sends status updates on Telegram.

## Specification
- What it does: You save time on manual data entry by letting this agent ingest your documents to extract text, numbers, and key details automatically. It then routes the structured information via email and keeps you updated with real-time status messages on Telegram.
- Trigger: Triggered by an event (Manual · on document upload)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Mistral Cloud Chat Model: OCR and text extraction from documents
  - OpenAI Chat Model: AI processing of extracted data
  - n8n: Workflow automation and orchestration
  - Gmail: Sending processed documents and data
  - Telegram: Real-time alerts and status notifications

## Known pitfalls, handle each one explicitly in your implementation
1. OCR accuracy drops significantly on low-resolution scans, so implement a pre-processing step to enhance image clarity.
2. PII data exposure risks exist when sending documents via email, ensure end-to-end encryption or mask sensitive fields in the output.

## Reference implementation
https://n8n.io/workflows/4933 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/document-parsing-data-extraction-with-ocr/ via usecasesforagents.com