Protect Sensitive Data Without Losing Its Value.
Detect, mask and de-identify personally identifiable information across enterprise data, applications, analytics and AI workflows — helping your teams use data without unnecessarily exposing sensitive information.
PII • PHI • Data Masking • De-Identification • AI & LLM Data Protection • Secure Data Sharing
See How AI-Driven PII Protection Works.
Don't make visitors imagine the workflow. Let them see sensitive information identified, protected and converted into a safer version in seconds.
The system identifies information that requires protection.
The resulting data can be evaluated for its intended workflow.
This is an illustrative interface using fictional sample data. Actual detection, protection techniques and integrations should be configured for the organization's data, workflow and requirements.
Looking for a Broader AI Solution?
If your requirement goes beyond sensitive-data protection, explore the Performix AI services that can help you plan, build, govern and scale AI across your business.
Real Data Challenges. Practical Outcomes.
Data protection rarely starts with a technology decision. It usually starts with a problem a team needs to solve.
We had useful customer datasets sitting on the sidelines because nobody was comfortable using them for broader analytics. The difficult part was deciding what really needed to be hidden and what could stay. The Performix team worked through those questions with us and helped us arrive at a masking approach that kept the data useful.
Our developers were constantly asking for production-like records because synthetic data wasn't giving them enough to work with. At the same time, handing over real customer information wasn't an option. Performix showed us how we could create a safer middle ground with realistic, de-identified datasets. It made the conversation with our development teams much easier.
We were looking at security from the model side and hadn't really considered everything happening before the prompt reached the AI. That changed when we mapped our data and RAG workflow with Performix. We could see exactly where sensitive information might enter the process and where controls would make the most sense.
PII Doesn't Stay in One Place.
Sensitive information can move through databases, documents, analytics platforms, applications, third-party systems and modern AI pipelines. Protection needs to follow the data wherever it is processed.
Enterprise Databases
Protect customer, employee, patient and operational information across data environments.
Documents & Files
Identify sensitive information in unstructured documents and other business content.
Analytics
Prepare safer datasets for analytics, reporting, testing and collaboration.
AI & LLM Pipelines
Reduce sensitive-data exposure across prompts, retrieved content and AI application workflows.
RAG Applications
Apply protection to sensitive information entering retrieval and knowledge workflows.
Third-Party Sharing
Protect sensitive fields before data is shared with external teams, vendors or partners.
Detect Sensitive Data. Mask It. Keep It Useful.
Build data-protection workflows around the type of information, use case, risk level and protection policy your organization requires.
AI-Assisted PII Detection
Identify sensitive information using intelligent detection approaches across supported data types.
Context-Aware Classification
Use context to improve identification of sensitive information beyond simple field matching.
Intelligent PII Masking
Apply configurable masking policies based on data type, workflow and protection requirements.
Tokenization
Replace sensitive values with controlled representations where tokenization is appropriate.
Anonymization & De-Identification
Prepare data for appropriate downstream use while reducing direct exposure of identifiers.
Audit-Ready Protection
Maintain visibility into protection activity and configured data-protection operations.
Protect PII Across Modern AI Workflows
AI systems introduce new paths for sensitive information to enter prompts, retrieved content, context windows and generated outputs. PII protection can become a layer within the broader AI application and data-security architecture.
Where It Can Help
• LLM applications
• RAG pipelines
• AI agents
• Prompt and document workflows
• AI-enabled enterprise applications
• Data preparation for AI development
Protect Data Without Automatically Throwing Away Its Value
Not every protection requirement calls for deleting an entire record. Depending on the use case, data can be protected through techniques such as masking, tokenization, generalization or de-identification while retaining useful characteristics for legitimate analytics, research, testing and application workflows.
Built for Data-Intensive Organizations
Use PII protection wherever sensitive information needs to be processed, analyzed, shared or introduced into modern AI workflows.
Healthcare & Life Sciences
Protect patient and research information across analytics, collaboration and AI workflows.
- Patient data
- Research datasets
- Clinical workflows
- Analytics
Financial Services
Reduce exposure of customer and financial information across data environments.
- Customer data
- Analytics
- Model development
- Third-party sharing
Insurance
Protect policyholder and operational information while enabling legitimate data workflows.
- Claims data
- Customer records
- Analytics
- Testing
Enterprise AI Teams
Build privacy controls into LLM, RAG and AI application workflows.
- LLM applications
- RAG
- AI agents
- AI data preparation
AI-Driven PII Protection vs. Traditional Masking
Different approaches solve different problems. The right architecture depends on the type of data, workflow and protection objective.
| Capability | Traditional Masking | AI-Driven PII Protection |
|---|---|---|
| Structured data protection | ✓ | ✓ |
| Unstructured data | Limited | AI-assisted |
| Context-aware detection | Limited | Designed for |
| AI / LLM workflows | Limited | Designed for |
| PII classification | Often rule-based | AI-assisted options |
| Masking / tokenization | ✓ | ✓ |
| Auditability | Varies | Configurable |
| RAG protection | Limited | Architecture dependent |
Make PII Protection Part of Your Data Governance Strategy
PII protection works best when technology, policies and operational controls are designed together.
Access Controls
Design role-based access and authorization around protected data workflows.
Identity Integration
Connect supported enterprise identity and authentication workflows where required.
Audit Logs
Track relevant data-protection activity for operational and governance review.
Protection Policies
Define masking and handling rules based on data type and business use case.
AI Governance
Consider sensitive-data controls as part of the wider AI application architecture.
Deployment Options
Evaluate the appropriate deployment and data-residency model for your environment.
PII Protection Designed Around Your Real Data Workflows
Performix combines AI, enterprise software engineering and data-focused solution development to help organizations build practical protection into the applications, data workflows and AI initiatives they already use.
Business-First Architecture
Start with the data, users and workflows that need protection — not just a technology layer.
AI + Enterprise Engineering
Connect PII protection with modern AI and enterprise application environments.
Designed for Integration
Scope protection around existing data platforms, applications and AI workflows.
Questions Buyers Ask About AI-Driven PII Protection
Protect Your Data Without Slowing Down Your Business.
See how AI-driven PII protection can help secure sensitive information across enterprise data, analytics, applications and modern AI workflows.
Book a Demo →Protect Sensitive Data with AI
See how Performix can help identify sensitive PII, anonymise data and keep it useful across your applications and AI workflows.
