Reddit user pulls health data from 3 sources with OpenClaw for cardiology appointment

OpenClaw pulled together health data from three different sources for a cardiology follow-up appointment, as described in a recent r/openclaw post. The user gave the tool a doctor's PDF, an export from a fitness watch, text messages containing medication info, and handwritten notes about appointment history. OpenClaw resolved a conflicting appointment date, built the requested Excel workbook in DD-MM-YYYY format, and emailed it to the doctor's office — all without the user providing the actual email address.

Key capabilities demonstrated

• Multi-source data ingestion: Handled a PDF, fitness watch export (with four different date formats), SMS texts, and handwritten notes.
• Date conflict resolution: Ignored the handwritten notes that had a wrong appointment time and deferred to the calendar entry.
• Data filtering: Removed a warm-up segment from the exercise data that wasn't a real workout.
• Deduplication: Merged walking and yoga data from separate sources without duplicates.
• Privacy preservation: Automatically excluded financial information from spousal texts that was mixed in with medication reminders.
• Automatic email discovery: Found the doctor's office email address from context, since the user only said “send it to the office”.
• Proactive reminders: Set a reminder for the morning before the appointment to skip exercise that day.

Practical implications

For developers building health data integration tools, this case highlights the importance of handling inconsistent date formats, resolving entity conflicts from unstructured text, and ensuring sensitive data is filtered during multi-source merges. The fact that OpenClaw could infer the email address and ignore wrong calendar entries suggests it uses some form of context-aware reasoning beyond simple keyword matching.