Turn clinical data into working AI without the privacy risk
Remove PHI from records, conversations, and patient data so you can build AI, analyze outcomes, and share with partners.
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Trusted by
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From Protected to Production-Ready
Three steps to compliant, usable clinical data, whether you're building AI models, running research, satisfying an auditor, or sending transcripts to external services.
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Detect PHI Across Every Record
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De-identify Without Losing Clinical Value
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Prove Your Compliance Holds Up
Built for How Clinical Data Actually Looks
Multilingual physician notes, annotated scans, real-time patient conversations, AI scribe transcripts, DICOM metadata. Clinical data hides PHI in places generic tools miss.
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Process Any Clinical Format
Real-Time Masking for Patient-Facing AI
Your Infrastructure, Complete Control
Your Clinical Context Stays Intact
Accuracy That Matters for Compliance
Providence Health
99.5%+
0
Shipped
The AI was ready. The data wasn't.
Years of valuable clinical data sat unused because it contained too much PHI to safely feed into AI models. Providence wanted to build a smart assistant for physicians using EHR data and conversation transcripts, but privacy requirements had the project stuck in limbo.
Limina unlocked it.
Limina automated PHI removal from physician conversations and EHR records entirely within Providence's own environment. Providence evaluated major cloud providers but rejected them over data usage concerns. Container deployment meant sensitive data never left their infrastructure.
Limina's integration was seamless and exactly what we needed to scrub all the PII out of our datasets.
Development Manager,
Providence
Frequently Asked Questions
What PHI does Limina detect in healthcare data?
What PHI does Limina detect in healthcare data?
Over 50 entity types covering PHI, PII, and PCI across 52 languages. Standard identifiers include names, dates of birth, addresses, and government IDs. Healthcare-specific detection covers medical record numbers, prescription identifiers, clinical codes, and insurance IDs. We also catch context-specific PHI in conversational patient language—with typos, code-switching, and incomplete descriptions—that generic tools miss.
How does de-identification preserve clinical value?
How does de-identification preserve clinical value?
De-identification removes what identifies patients, not what describes their clinical condition. Diagnoses, symptoms, treatments, lab results, and clinical assessments stay intact. Date shifting maintains temporal relationships. Pseudonymization tracks patients across encounters without storing real identities. Synthetic PII replacement preserves the statistical shape of your dataset while eliminating re-identification risk.
What HIPAA standards does Limina meet?
What HIPAA standards does Limina meet?
Both Safe Harbor and Expert Determination. Safe Harbor removes all 18 HIPAA-defined identifiers automatically. For Expert Determination, we provide expert determination-ready outputs and formal reports through our partner network—with independent statistical validation that proves re-identification risk is very small. Major pharmaceutical companies use these outputs for FDA submissions. Research institutions use them for IRB review and data sharing with external partners.
Can we use Limina for real-time AI scribe and chatbot workflows?
Can we use Limina for real-time AI scribe and chatbot workflows?
Yes. Limina masks PHI in doctor-patient conversations as they're transcribed, so clean output goes to your AI platform without identifiers. For patient-facing chatbots, we sanitize inputs before they reach models and can validate responses before patients see them. Processing happens inside your environment—PHI never flows to external AI services before it's protected.
Does our data leave our environment?
Does our data leave our environment?
No. Limina deploys as a container in your on-premises environment or VPC. All processing happens inside your existing security perimeter. No third-party cloud processing, no external transmission. Providence Health specifically chose this model because major cloud providers wanted rights to use patient data for model training.
Can we use de-identified data for AI training, research, and FDA submissions?
Can we use de-identified data for AI training, research, and FDA submissions?
Canadian research consortia use it for collaborative LLM training across institutions. Pharmaceutical companies use expert determination outputs for FDA submissions and clinical trial analysis. Expert determination documentation proves your training data are defensible for commercial use, research, and regulatory review.