CONTACT CENTERS

Your Best Customer Insights Are Locked in Conversations You Can't Use

Remove PII, PHI, and PCI from call transcripts, chat logs, and customer interactions so your analytics, AI, and QA teams can work with real conversations—accurately, compliantly, and entirely within your infrastructure.

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Built for

HOW IT WORKS

From Transcripts to Insights

Three steps to compliant, usable contact center data whether you're storing transcripts for QA, training AI on real conversations, or meeting PCI DSS requirements for call handling.

Detect Sensitive Data in Conversational Speech

Catch credit cards read digit by digit, account numbers corrected mid-sentence, and PHI mixed into service requests. Handle the way customers actually talk, not just perfectly formatted sensitive data in structured fields.

Remove Compliance Risk, Preserve Conversation Value

Redact, pseudonymize, or tokenize sensitive data while keeping agent tone, customer sentiment, resolution patterns, and service context intact. QA teams, analytics platforms, and AI models get what they need. Regulators get nothing they shouldn't see.

Clean Data Into Your Existing Stack

De-identified transcripts flow directly to your CRM, quality management platform, workforce optimization tools, and data warehouse. No rearchitecting your contact center stack, just cleaner data flowing through it.

Built for Contact Centers Operating at Scale

Calls where customers read credit card numbers digit by digit. Years of archived transcripts that compliance never cleared for AI training. Hundreds of thousands of interactions daily that need protection before storage.

Real-Time Redaction for Live Operations

Process call transcripts as they stream from your speech-to-text engine. Payment data get redacted before transcripts reach your CRM, analytics platform, or data warehouse, removing those systems from PCI DSS scope.

Unlock Historical Archives for AI and Analytics

Years of call transcripts contain valuable training data for AI models, fraud detection, and service improvement, but PII makes them too sensitive to use. Batch processing handles legacy archives at scale, cleaning up data that was stored before privacy controls existed.

QA and Analytics Without Compliance Risk

Redacted conversations preserve everything QA teams need: agent tone, empathy, problem-solving approaches, script compliance, resolution effectiveness, and customer sentiment. Format-preserving pseudonymization lets you track the same customer across multiple interactions without storing their real identity. Analyze service quality and train agents on real conversations without accessing sensitive customer data.

Your Infrastructure, Complete Control

Deploy on-prem or in your VPC. Call transcripts, chat logs, and customer communications never leave your infrastructure during de-identification. No third-party cloud processing, no external transmission. This architecture keeps you inside PCI DSS scope requirements and satisfies data residency rules for contact centers operating across jurisdictions.

52 Languages for Global Operations

Process customer interactions in English, Spanish, French, Japanese, and 49 other languages. Detect region-specific identifiers—Canadian SINs, European IBANs, Japanese personal identifiers alongside standard PCI and PHI. Handle code-switching when agents and customers mix languages mid-conversation, which happens constantly in multilingual contact centers.

CUSTOMER WIN

Major Contact Center Services Provider

99.5%+

Accuracy on target entities in Japanese call data

Years

Of archived call data unlocked for AI and analytics

Real-time

De-identification now applied to every new call before storage

Years of Call Data. No Way to Use It.

A global contact center provider wanted to build AI-driven call summaries to improve performance and customer satisfaction, but years of unstructured Japanese call transcripts contained customer PII that blocked safe storage and analysis. Manual and Python-based redaction tools lacked the accuracy and scalability the volume required.

Limina Unlocked the Archive

Limina de-identified years of accumulated Japanese call data with custom rules for contact center language, catching PII in natural conversational speech where standard tools failed. Container deployment kept all data in-house. With the archive clean, the contact center now applies real-time de-identification prior to storage on every new call, turning compliance into a foundation for AI development rather than a barrier to it.

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Ready to Put Your Contact Center Data to Work?

Talk to our team about your use case. Most customers are up and running in days, not months.

Frequently Asked Questions

What customer data should contact centers protect?

Payment information—credit cards, CVVs, bank accounts—for PCI DSS compliance. Healthcare details—diagnoses, medications, medical record numbers—for HIPAA compliance in healthcare support centers. Account numbers, SSNs, addresses, and personal identifiers that create privacy risk when stored in CRM systems and quality management platforms. Beyond standard identifiers, Limina catches partial information like "card ending in 4532" and conversational fragments where customers share sensitive details across multiple sentences.

How does call transcript redaction affect PCI DSS scope?

Transcripts containing credit card numbers bring your call analytics platform, CRM, and data warehouse into PCI scope with extensive security requirements. Redacted transcripts containing no payment data fall outside scope entirely—you store calls for QA, fraud pattern analysis, and agent training without PCI audit obligations applying to those downstream systems. This reduces compliance costs and simplifies security architecture for every system that only needs call content, not payment data.

How does Limina handle payment data the way customers actually say it?

Customers don't read card numbers in clean sequences. "My card is 4-5-3-2, wait, sorry, 4-5-3-3" gets detected. "The last four digits are 9-0-1-0" triggers redaction. Numbers split across sentences, corrected mid-reading, or referenced as "card ending in 4532" are all caught. Limina handles real-world speech patterns rather than only catching perfectly formatted card numbers read in sequence.

Can we still do quality assurance on redacted conversations?

Yes. Redacted conversations preserve everything QA teams need except customer identities and payment details. Agent tone, empathy, problem-solving approach, script compliance, resolution effectiveness, and customer sentiment all remain analyzable. Format-preserving pseudonymization lets you track the same customer across multiple interactions without storing their real name. QA teams evaluate agent performance without needing access to sensitive customer data.

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. This matters especially for contact centers: call transcripts, chat logs, and customer communications never flow to external services before they're protected.

How does Limina handle multilingual contact center operations?

Limina works across 52 languages with region-specific detection for financial and personal identifiers across North America, Europe, Asia, and Latin America. Canadian SINs, UK NHS numbers, European IBANs, and Japanese personal identifiers are all detected alongside standard PCI from a single deployment. The system handles code-switching when agents and customers mix languages mid-conversation—common in multilingual contact centers and global support operations.