Data Vault Security
Enable secure AI use across your organization. Protect sensitive data while maintaining access to leading foundation models.
The Shadow AI Challenge
Research from KPMG indicates that 57% of employees conceal their AI tool usage from employers, while 46% of UK workers have uploaded sensitive business information to these services. This creates a governance challenge: your team gains productivity benefits while potentially creating regulatory exposure.
Prohibiting AI use rarely proves effective. Your competitors likely use these tools, your team will find workarounds, and you forgo legitimate productivity gains. The more practical approach involves enabling compliant AI use through appropriate technical controls.
The Solution: Intelligent Governance Layer
Your team likely already uses AI tools—ChatGPT, Claude, Copilot, Gemini. Data Vault provides the governance layer that makes this use compliant and secure, automatically filtering sensitive information while preserving productivity benefits. It works alongside both public AI services and private infrastructure, giving you flexibility as your AI strategy evolves.
Data Vault sits between your users and AI services, identifying and filtering sensitive information in both directions, enforcing your usage policies, and maintaining comprehensive audit trails. Your team continues using familiar AI interfaces with minimal workflow disruption. The protection operates transparently, intervening only when necessary to prevent sensitive data exposure.
Sensitive Data Detection
Identifying information requiring protection
Personal Data
Names, addresses, contact details, identification numbers, financial information. Automatically detected using pattern recognition and contextual analysis.
Commercial Information
Pricing data, contract terms, strategic plans, customer lists. Identified through custom rules you define based on your business requirements.
Special Category Data
Health information, biometric data, political opinions. Requires heightened protection under UK GDPR Article 9.
Professional Privilege
Legal advice, client communications, case strategy. Critical for law firms and professional services maintaining confidentiality obligations.
Policy Enforcement
Applying your organisation's rules.
Usage Policies
Define which AI services staff may access, which use cases are permitted, and any restrictions specific to roles or departments.
Data Handling Rules
Specify how different data categories should be treated—block, redact, tokenize, or allow with logging based on sensitivity and context.
Output Controls
Monitor AI responses for inappropriate content, potential hallucinations, or inadvertent disclosure of information from other users' queries.
Compliance Controls
Enforce industry-specific requirements—FCA record-keeping, SRA confidentiality, CQC information governance, or sector-specific data protection standards.
Comprehensive Logging
Creating audit trails for compliance.
Complete Interaction Records
Every query, response, and policy decision logged with timestamps and user identification.
Data Protection Events
Sensitive data detections, redactions, and blocks documented for DPIA and audit purposes.
Regulatory Reporting
Generate reports demonstrating compliance with UK GDPR, industry regulations, and internal policies.
Incident Investigation
Detailed records enable rapid response to data protection concerns or regulatory inquiries.
Frequently asked questions.
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Blocking AI tools typically drives usage underground rather than eliminating it. Staff use personal devices, home networks, or unauthorized services—creating greater risk with zero visibility. Data Vault enables legitimate, productive AI use while maintaining appropriate controls and audit trails.
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Technical controls prevent direct access to AI services from corporate networks and devices. Staff would need to use personal devices on non-corporate networks—the same circumvention possible with any security control. Data Vault significantly raises the barrier while enabling legitimate use, reducing motivation for circumvention.
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Yes. Data Vault integrates with private LLM infrastructure, providing an additional governance layer. Even with complete infrastructure control, Data Vault adds policy enforcement, prevents accidental exposure, and maintains comprehensive audit trails. Many organizations use Data Vault with both private and public AI services simultaneously.
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Depending on your policy configuration: block the query entirely, redact sensitive portions while allowing the query to proceed, tokenize data for AI processing then de-tokenize results, or allow with enhanced logging. You define rules based on data sensitivity, user roles, and business context.
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Detection combines pattern matching (high accuracy for structured data like email addresses, phone numbers), contextual analysis (good accuracy for personal names, addresses), and custom rules you define (accuracy depends on rule specificity). We tune detection thresholds during implementation to balance protection with usability for your specific environment.
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Yes. Define different policies for different user groups, departments, or use cases. For example: finance team may have stricter controls than marketing, legal department may require enhanced privilege protection, or senior management may have broader permissions with enhanced monitoring.