PDF→Markdown tooling that strips sensitive data before cloud AI processing, so document-heavy workflows can use LLMs without treating privacy as an afterthought.
PDF → Markdown
Auto anonymization
Pre-cloud gate
Safer AI adoption
Context
Operations teams needed AI support for document-heavy work, but sending raw operational documents to cloud LLMs created unacceptable privacy exposure.
Intervention
Built a PDF-to-Markdown toolbox with automatic anonymization that removes sensitive fields before any cloud LLM step—making privacy a pipeline stage, not a policy memo.
Outcome
Before: privacy risk blocked useful AI adoption. After: faster document turnaround with a clear pre-processing gate that reduces exposure before cloud inference.
System map
Sensitive content is removed before the cloud boundary—not after a leak.