How accurate is Limina compared to manual redaction and other similar products?

Limina achieves 99.5% accuracy on physician conversations, as demonstrated in deployment with Providence Health.

Does my data leave my environment?

No. Limina's container runs in your VPC or on-premise. Data never leaves your infrastructure.

What languages and data formats does Limina support?

Limina supports 52 languages and works across structured and unstructured data including text, images, audio, and documents. It handles multilingual content and code-switching.

Which compliance standards does Limina meet?

Limina provides independent expert determination reports for HIPAA, GDPR, CPRA, and other global privacy regulations.

Can I use de-identified data for AI training, analytics, and data sharing?

Yes. Limina's context-aware de-identification preserves data utility while removing sensitive information, making it suitable for AI training, analytics, and compliant data sharing.

How accurate is Limina compared to manual redaction and other similar products?

Limina achieves 99.5% accuracy on physician conversations, as demonstrated in deployment with Providence Health.

Does my data leave my environment?

No. Limina's container runs in your VPC or on-premise. Data never leaves your infrastructure.

What languages and data formats does Limina support?

Limina supports 52 languages and works across structured and unstructured data including text, images, audio, and documents. It handles multilingual content and code-switching.

Which compliance standards does Limina meet?

Limina provides independent expert determination reports for HIPAA, GDPR, CPRA, and other global privacy regulations.

Can I use de-identified data for AI training, analytics, and data sharing?

Yes. Limina's context-aware de-identification preserves data utility while removing sensitive information, making it suitable for AI training, analytics, and compliant data sharing.

PII REDACTION

Redact PII from every document, transcript, and image you hold.

Context-aware ML finds and removes personal data across 50+ entity types and 52 languages, running entirely inside your own environment.

TALK TO AN EXPERT

30-minute call with a Limina engineer. No deck, no discovery script.

For data, security and compliance teams handling regulated or sensitive data at volume.

IMPACT

0.2 - 7%

PII missed by Limina, against 13.8 - 46.5% by general-purpose tools

70,000

words per second redacted on GPU

50+

entity types across 52 languages

2

Docker commands to deploy in your own VPC

From Restricted to Ready

Detect What Matters

Accurate until volume arrives. Then it is a backlog with a headcount line attached.

Transform for Your Use Case

100+ patterns, a dedicated bug channel, and no way to catch what context reveals.

Deploy in Your Environment

Built for breadth, not for PII. The miss rate shows it.

Built for Real-World Data

Blue square with a black plus symbol partially overlaid by a tilted light blue eraser.

Detect what matters

Context-aware ML identifies PII, PHI and PCI across 50+ entity types the way a trained reviewer would. Coreference resolution links names, abbreviations and variations so nothing slips through.

Choose how it is removed

Redact, pseudonymize, tokenize reversibly, or replace with synthetic data that preserves the statistical shape of the dataset. Configure per entity type, per workflow.

Run it in your environment

A single container in your cloud, VPC or on-prem infrastructure. Two Docker commands. Data never leaves your environment.

Talk to an Expert

CUSTOMER WIN

Providence Health

99.5%+

Accuracy on target PHI entities

0

Exposed data to third parties

Shipped

An AI-powered physician assistant

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.

Wayne Foley

Senior Software
Development Manager,
Providence

Your data never leaves your environment.

Container-based deployment means all processing stays in your VPC or on-premises infrastructure. No third-party access. No outbound data calls. Ever.

Ready to see it run on your data?

A 30-minute call with a Limina engineer or solutions expert. No deck. No discovery script. We'll ask what you're working on, where you're stuck, and whether Limina is the right fit.

What you leave with

What accuracy to expect on your data type
A deployment path for your environment
A realistic timeline to production

Questions we get before the first call

How accurate is it compared with AWS Comprehend, Google DLP or Presidio?

We tested approximately 45,000 words across multiple real-world domains, comparing Limina against major cloud providers' general-purpose PII detection tools. The results show why specialization matters.