Walled RedactComplete Sensitive Data Protection for Carefree LLM Integrations
Mask -> Prompt ->Unmask
Detect and mask personally identifiable information, client and patient data, deal terms and other business-sensitive information, trade secrets, and more - BEFORE any of it reaches an LLM
Conversations Protected
Trusted By
Meticulous Protection for PII and Every Other Secret
It's not just personal data. Client and patient identities, negotiation and deal terms, contract values, source code, and other business-sensitive information are just as exposed in an AI prompt. Walled Redact protects all of it across every mode of LLM interaction - emails, audio transcripts, screenshots, source code, and more - with redaction support across 15+ Modalities and 50+ Entity Types.
Real-time detection and masking of PII, financial data, and trade secrets in text prompts, chat conversations, and email drafts.
Four Simple Steps to Foolproof Data Protection
Start
A prompt is about to reach an LLM - typed by an employee, or generated mid-task by an AI agent
Intercept
Walled Redact intercepts the query before it reaches the LLM
Detect & Classify
Our proprietary prompt and document classification engine identifies sensitive information across text, images, code, audio, and other modalities
Mask Before Prompting
Sensitive values are masked and replaced with secure placeholder tokens before the prompt reaches the LLM
Unmask & Deliver
The LLM's response is intercepted and the placeholder tokens are restored to their original values before delivery, maintaining format fidelity
Start
A prompt is about to reach an LLM - typed by an employee, or generated mid-task by an AI agent
Intercept
Walled Redact intercepts the query before it reaches the LLM
Detect & Classify
Our proprietary prompt and document classification engine identifies sensitive information across text, images, code, audio, and other modalities
Mask before Prompting
Sensitive values are masked and replaced with secure placeholder tokens before the prompt reaches the LLM
Unmask and deliver
The LLM's response is intercepted and the placeholder tokens are restored to their original values before delivery, maintaining format fidelity
Mask Before AI. Unmask For People.
The LLM only ever processes placeholder tokens. The real names, companies, and figures are restored only in what the employee sees on the way back - the model never has access to them.
Mask before AI, unmask for people: sensitive data is restored only in what the employee sees - the LLM never has access to it.
One of the Only On-Premises Data Protection Solutions
Tap into the power of LLMs without compromising AI data privacy. Walled Redact is one of the few sensitive-data protection solutions - covering PII, client data, and business-sensitive information - that is 100% deployable within enterprise premises.
Keep your data within your organization's boundaries while securely accessing external LLM capabilities
Why Walled Redact Works
LLMs need Context, Not Content. LLMs don't need your actual customer names, account numbers, or proprietary data to generate useful responses. They need the structure and context of your query.
When an employee asks "Draft a follow-up email to John Smith at Acme Corp about his $2.4M account renewal," the LLM doesn't need to know it's John Smith or $2.4M. It needs to know this is a follow-up, about a named person, at a named company, regarding a high-value renewal.
❌ Without Walled Redact
"Draft a follow-up email to John Smith at Acme Corp regarding his $2.4M account renewal, reference account #AC-4829."
✅ With Walled Redact
"Draft a follow-up email to [PERSON_1] at [ORG_1] regarding his [AMOUNT_1] account renewal, reference account [ID_1]."
The LLM generates an equally good email - and your employee sees the final output with all real values restored. Zero compromise on productivity. Zero data exposure.
Privacy that Doesn't Compromise on Performance
Privacy shouldn't come at the cost of performance. Walled Redact is lightweight, lightning-fast, and low latency. Ensure your team's productivity remains unhampered while enabling complete AI data privacy.
Performance comparison across different use cases: Detection Latency (ms), Throughput (req/sec), Accuracy (%)
Walled Redact vs Private LLMs
Burning your enterprise budget on Private LLMs?
Switch to Walled Redact's flexible and inexpensive deployment solutions that enable complete AI data privacy at a fraction of the cost.
| Capability | Private LLM | Walled Redact |
|---|---|---|
| Infrastructure Cost | $500K–$2M+ annual | A fraction of the cost |
| Deployment Timeline | 6–12 months | Days |
| Model Freshness | Obsolete in 6–8 months | Always the latest |
| Team Requirements | Dedicated ML engineers | No specialists needed |
| Model Access | 1–2 model families | GPT, Claude, Gemini, Llama, etc. |
| Latest Capabilities | ❌ No | ✅ Yes |
| Security Burden | Ongoing maintenance | Handled by WalledAI |
Fine-tuned Data Protection for Every Industry
Whether it's regulatory compliance in finance or PHI protection in healthcare, Walled Redact's flexible policy engine is precisely calibrated for what matters the most to your business. Role-based access controls offer further fine-tuning of which teams see what data.
| Industry | What Gets Protected? |
|---|---|
| All Industries | Personally Identifiable Information (PII), client and customer information, business-sensitive deal terms, trade secrets & IP, proprietary business logic, contracts, strategy documents |
| Financial Services | Client names and identities, account numbers, portfolio values, deal and transaction values, financial figures |
| Healthcare | Patient names and identities, Diagnosis codes, Lab results |
| Legal | Client names and identities, Counterparty names, Deal values, Privileged communications |
| Enterprise HR | Employee names, Performance ratings, Salary data |
10+ Predefined Policies, Wherever You Operate
Walled Redact ships with 10+ predefined masking and governance policies mapped to the regulations your business already answers to - so day one enforcement isn't a blank policy engine. Layer your own custom policies and governance rules on top for anything sector- or company-specific.
United States
- CCPA / CPRA
California Consumer Privacy Act & Privacy Rights Act
- VCDPA
Virginia Consumer Data Protection Act
- CPA
Colorado Privacy Act
- CTDPA
Connecticut Data Privacy Act
- UCPA
Utah Consumer Privacy Act
- HIPAA
Health Insurance Portability and Accountability Act
- GLBA
Gramm-Leach-Bliley Act (financial services)
European Union
- GDPR
General Data Protection Regulation
- EU AI Act
Data governance & transparency obligations
Asia-Pacific
- PDPA
Singapore Personal Data Protection Act
- DPDP Act
India's Digital Personal Data Protection Act
Beyond the predefined set: your own policies
Define custom entity types, masking rules, and governance policies for whatever is specific to your business - a proprietary deal-naming convention, an internal project codename scheme, an industry framework we haven't named here. Predefined policies get you covered on day one; custom policies make sure nothing sector-specific slips through.
Ready to try Risk-free Data Protection?
See how Walled Redact masks sensitive data in real-time.
Data Protection Success Stories
Global Investment Bank Secures Client Data
Healthcare Provider Enables AI Without PHI Exposure
Law Firm Accelerates Deal Review with Protected Data
Learn More about AI Data Protection
WalledEval: A Comprehensive Safety Evaluation Toolkit
Our open-source framework for evaluating LLM safety guardrails - the research behind Walled Redact's detection models.
Read more about WalledEval: A Comprehensive Safety Evaluation ToolkitRead moreThe ROI of AI Governance
Why investing in a governance layer delivers 10x returns compared to restricting AI adoption or deploying private LLMs.
Read more about The ROI of AI GovernanceRead moreData Privacy in the Age of Agentic AI
As AI agents make autonomous decisions, the data exposure surface grows exponentially. How Walled Redact adapts.
Read more about Data Privacy in the Age of Agentic AIRead moreFrequently Asked Questions
What types of data can Walled Redact mask?
Walled Redact masks PII across 10+ modalities: text, images, documents (PDF, DOCX), code (50+ languages), and audio. It detects names, addresses, phone numbers, financial data, medical records, and custom entity types defined by your organization.
How does contextual restoration work?
When Walled Redact masks data before sending it to an LLM, it preserves a secure mapping. When the LLM responds, Walled Redact automatically restores the original values in the output - so your employees see real names and data, but the LLM never had access to it.
What is the accuracy of Walled Redact?
Walled Redact achieves 98.2% PII detection accuracy across all supported modalities, with sub-30ms processing latency. This includes edge cases like handwritten text in images, embedded data in PDFs, and comments in source code.
Does Walled Redact protect more than just PII?
Yes. Beyond personally identifiable information, Walled Redact masks client and patient identities, business-sensitive deal terms and contract values, trade secrets, proprietary business logic, and other confidential data before it reaches any LLM - across text, images, code, audio, and documents.
Which regulations does Walled Redact ship predefined policies for?
Walled Redact includes 10+ predefined masking and governance policies out of the box, covering US state and federal laws (CCPA/CPRA, VCDPA, CPA, CTDPA, UCPA, HIPAA, GLBA), the EU's GDPR and EU AI Act, Singapore's PDPA, and India's DPDP Act. You can also define custom policies and governance rules for anything specific to your business or industry.