TRUSTED BY BOEHRINGER INGELHEIM, ZURICH AND MUFG

Your Best Data Is Off-Limits. Until Now.

Turn your most restricted data into a valuable asset. Limina understands context, so nothing gets lost in redaction.

IMPACT

Proven at Scale

99.5%

Accuracy on physician conversations for Providence Health

48 hours → minutes

Medical inquiry response time for Boehringer Ingelheim

Billions

API calls processed per month in production
THE PROBLEM

Sound Familiar?

Cloud tools miss too much. DIY costs too much to maintain. And de-identification destroys the data you needed in the first place.

Cloud APIs aren’t cutting it

AWS Comprehend missed the SSN because "SSN" wasn't in the sentence. Presidio flags order numbers as credit cards. Every API call sends your data somewhere you don't control.

It started as a script

It handles text. Then JSON. Then audio. Then a new language. Each one a new edge case. Each one someone's problem to maintain.

De-id killed the data

You're HIPAA, GDPR, or CCPA compliant. Your data is also unusable. You don't have to choose between compliance and useful data.

Most tools match patterns.
We read context.

Most PII tools match formats. We read context, catching names that don't look like names, entities across sentences, credit cards spoken across turns. Context stays intact, so your data stays valuable.

Tools

Limina Capabilities

De-identification that works across your structured and unstructured data in any language, at any scale.

50+ Entity Types

PII, PHI, PCI in one API. Names, SSNs, credit cards, conditions, medications, passport numbers, plus international variants.

52 Languages

Deployed in US, Canada, UK, Germany, Japan, Hong Kong, Australia, Switzerland. Handles multilingual and code-switching.

Your Infrastructure

Container runs in your VPC or on-prem. Data never leaves your infrastructure.

Built for Messy Data

ASR errors. OCR mistakes. Handwritten forms. Conversational disfluencies. The stuff that breaks other tools.

Plugs into Your Stack

AWS, Azure, Snowflake, NVIDIA NeMo. No rework required.
TESTIMONIALS

What Our Customers Say

Trusted by enterprise leaders in healthcare, pharma, finance, and technology to activate regulated data safely.

Our platform reduces response time from days to minutes, but we couldn't have launched without proper anonymization. It was critical for compliance, especially to include US data, which represents one of our larger customer bases.

Israel Gonzales Salas
Data Engineer, Boehringer Ingelheim

Now our PHI detection accuracy is through the roof and our privacy team is happy. Limina was remarkably easy to integrate into our existing workflows, which saved us a lot of time and effort compared to maintaining our in-house solution.

Sebastian Walter
Chief Data Engineer, Semalytix

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
HOW IT WORKS

Deploy Anywhere. Unlock Data at Scale.

IDENTIFY

Spot Sensitive Data the Moment It Appears

Real-time detection of PII, PHI, and PCI across 50+ entity types, with data linking that connects related information. Turn unstructured text into structured intelligence you can actually use.

Raw text
Ronnie is a 39-year-old male, DOB 23 February 1986, residing at 4821 Cedarwood Drive, Austin TX 78745, presenting for follow-up of a right wrist fracture sustained during a zipline incident. Ronnie was referred by his GP, Dr. Patricia Holloway (NPI 1234567890), and his insurance claim #TXB-2026-00441 is currently under review by BlueCross BlueShield. Ronnie was placed in a short arm cast and instructed to mobilize fingers frequently, avoid lifting, driving, and keep the area dry using plastic wrap during bathing. On examination today, significant water damage is noted to the interior lining of the cast.
Entities identified
Ronnie is a 39-year-old male, DOB 23 February 1986, residing at 4821 Cedarwood Drive, Austin TX 78745, presenting for follow-up of a right wrist fracture sustained during a zipline incident. Ronnie was referred by his GP, Dr. Patricia Holloway (NPI 1234567890), and his insurance claim #TXB-2026-00441 is currently under review by BlueCross BlueShield. Ronnie was placed in a short arm cast and instructed to mobilize fingers frequently, avoid lifting, driving, and keep the area dry using plastic wrap during bathing. On examination today, significant water damage is noted to the interior lining of the cast.

Entities Found 16

TextEntity TypeConfidence
RonnieNAME_GIVEN90.71%
39-year-oldAGE94.00%
23 February 1986DOB92.11%
4821 Cedarwood Drive, Austin TX 78745LOCATION_ADDRESS91.65%
TRANSFORM

Remove or Replace What Shouldn't Be There

Redact, pseudonymize, generate synthetic PII, or generalize entities in EMRs, call transcripts, chat logs, and more. Get outputs ready for expert determination without the wait.

Entities identified
Ronnie is a 39-year-old male, DOB 23 February 1986, residing at 4821 Cedarwood Drive, Austin TX 78745, presenting for follow-up of a right wrist fracture sustained during a zipline incident. Ronnie was referred by his GP, Dr. Patricia Holloway (NPI 1234567890), and his insurance claim #TXB-2026-00441 is currently under review by BlueCross BlueShield. Ronnie was placed in a short arm cast and instructed to mobilize fingers frequently, avoid lifting, driving, and keep the area dry using plastic wrap during bathing. On examination today, significant water damage is noted to the interior lining of the cast.
Redacted
[NAME_GIVEN_1] is a [AGE_1]-year-old male, DOB [DOB_1], residing at [LOCATION_ADDRESS_1], presenting for follow-up of a [INJURY_1] sustained during a zipline incident. [NAME_GIVEN_1] was referred by his GP, [OCCUPATION_1] [NAME_MEDICAL_PROFESSIONAL_1] (NPI [NUMERICAL_PII_1]), and his insurance claim #[HEALTHCARE_NUMBER_1] is currently under review by [ORGANIZATION_1]. [NAME_GIVEN_1] was placed [MEDICAL_PROCESS_1] and instructed to mobilize fingers frequently, avoid lifting, driving, and keep the area dry using plastic wrap during bathing. On examination today, significant [INJURY_2] is noted to the interior lining of the cast.

Entities Found 16

TextEntity TypeRedacted As
RonnieNAME_GIVEN[NAME_GIVEN_1]
39-year-oldAGE[AGE_1]
23 February 1986DOB[DOB_1]
4821 Cedarwood Drive, Austin TX 78745LOCATION_ADDRESS[LOCATION_ADDRESS_1]
COMPLY

Show Auditors Exactly What They Need

Independent expert determination reports give auditors the evidence they need for HIPAA, GDPR, CPRA, and other global regulations. Built by privacy experts. Accepted by compliance teams.

IDENTIFY
IDENTIFY

Spot Sensitive Data the Moment It Appears

Real-time detection of PII, PHI, and PCI across 50+ entity types, with data linking that connects related information. Turn unstructured text into structured intelligence you can actually use.

TRY FOR FREE
TRY FOR FREE
TRANSFORM
TRANSFORM

Remove or Replace What Shouldn't Be There

Redact, pseudonymize, generate synthetic PII, or generalize entities in EMRs, call transcripts, chat logs, and more. Get outputs ready for expert determination without the wait.

TRY FOR FREE
TRY FOR FREE
COMPLY
COMPLY

Show Auditors Exactly What They Need

Independent expert determination reports give auditors the evidence they need for HIPAA, GDPR, CPRA, and other global regulations. Built by privacy experts. Accepted by compliance teams.

TRY FOR FREE
TRY FOR FREE
GET STARTED

Built for Regulated Industries

Audited, certified, and recognized by the institutions that regulate the data you work with.

Frequently Asked Questions

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

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.

General-purpose solutions miss between 13.8% and 46.5% of PII entities in real-world data. Limina misses between 0.2% and 7% across the same datasets. That difference is everything when missed PII can lead to data breaches, regulatory fines, and lost customer trust.

The biggest performance gap shows up in recall, which measures how much PII actually gets caught. Recall is the metric that matters most because every missed entity is a compliance risk. Six years of focused development on PII detection challenges produces fundamentally different results than general-purpose tools built for broader use cases.

We've gone head to head against other tools in POCs for the last 6 years, and the pattern holds: customers consistently choose Limina when they test accuracy on their own data.

Manual redaction is even worse. It's slow, expensive, and error-prone at scale. A major pharmaceutical company was spending 7 days on complex document redaction. With Limina, they reduced that to minutes while maintaining accuracy.

When a multinational insurance company tested other tools for Japanese data, they failed completely. Limina delivered the accuracy they were looking for.

Download our whitepaper for detailed methodology, results, and head-to-head comparisons.

Does my data leave my environment?

No. Your data never leaves your infrastructure.

Limina deploys as a container in your on-premises environment or VPC. Everything runs locally, so sensitive data is processed entirely within your existing security perimeter. No third-party cloud processing, no data transmission to external services (aside from simple usage statistics), not even to us.

This architecture meets data sovereignty requirements and gives you complete control over your compliance posture. Your data stay yours.

What languages and data formats does Limina support?

Limina works across 52 languages and multiple data formats: text, PDFs, images, audio, structured data, and more. We detect and de-identify 50+ entity types covering PII, PHI, and PCI across all supported languages.

We also support regional language varieties (like US/UK/Canadian English, or Spain/Mexico Spanish) and handle code-switching when people mix languages in the same sentence.

For the complete list of languages, entity types, and file formats, visit our documentation.

Which compliance standards does Limina meet?

Limina supports compliance with HIPAA, GDPR, PCI-DSS, CPRA, APPI (Japan), Law 25 (Quebec), and other global privacy regulations.

We provide expert determination-ready outputs that meet HIPAA's de-identification standard. Through our partner network, we also deliver formal expert determination reports with statistical validation and audit-ready documentation. Major pharmaceutical companies use us for FDA filings, financial services firms for PCI compliance, and healthcare providers for HIPAA Safe Harbor and Expert Determination.

Our technology has been independently validated by Armilla AI (backed by SwissRe), and we've created expert determination reports with partners like AETION for real client deployments.

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

Yes. That's exactly what it's designed for.

De-identified data from Limina preserves utility while removing privacy risk. Customers use it to train LLMs, power analytics, build AI products, and share data with research partners or across teams.

Expert determination-ready outputs mean your data are defensible for research, commercial use, and regulatory submissions. You get data you can actually use, not just redacted text that destroys all the value.