Zero-Trust Sanitization
for Academic Research.
Synthesize interviews, trial data, and academic transcripts with LLMs safely. Ensure IRB and FERPA compliance through offline data sanitization.
Industry Privacy Blind Spots
FERPA Violations
Exposing student names, ID numbers, or grades to unapproved AI platforms during grading or assessment generation.
Interview Transcript Leaks
Processing raw sociological or psychological research interviews with LLMs exposes vulnerable subject identities.
IRB Protocol Breaches
Uploading trial data to cloud AI services that train on user inputs violates strict Institutional Review Board anonymity constraints.
Input: Document concerning John Doe (A-123)
Input: Target concerning [NAME_1] ([ID_1])
Secure Processing Workflow
Offline data protection for compliance teams
Import Data
Bring documents into the secure local browser environment.
Local Masking
Redact PII locally, replacing identities with semantic tokens.
Secure LLM Call
Send only sanitized data to external models like ChatGPT or Claude.
Reverse Scrub
Restore original values into the AI response locally before delivery.
Regulatory Trust Framework
Compliant
Protect student education records
Compliant
Maintain human subject anonymity
Satisfied
Protect clinical trial health data
Satisfied
EU academic research privacy
ACADEMIC Deep-Dive
Can I use AI to summarize qualitative interviews?
Does this meet IRB anonymization requirements?
How do I process large datasets?
Deploy Secure AI Sanitization Today
Stop PII leakage at the edge. Secure your workflows locally.
GET STARTED — $9.99 ONE-TIME