Data De-Identification for Sensitive Data
De-identify sensitive data so it cannot be tied back to a person, while keeping a governed path to the real value for authorized identities. Ubiq protects the value itself, then returns either the unprotected value or a configured protected representation at runtime based on identity, context, and policy.
Trusted in production by security & data teams
Independently attested
SOC 2 Type II
PCI DSS SAQ-D
CMMC 2.0 Level 1What is data de-identification?
Data de-identification removes or transforms the identifiers that link a record to a specific person, so teams can run analytics, testing, AI, and data sharing without exposing who the data belongs to. Common techniques include masking, tokenization, pseudonymization, generalization, and redaction. Traditional de-identification is a one-way batch transform applied once for everyone. Ubiq goes further: it protects the value itself, then reveals the right version at runtime based on identity and policy.
Governed, reversible protection
Ubiq's model is governed and reversible: return the unprotected value when policy allows, or a configured protected representation when policy requires protection. Re-identification is controlled by identity and policy, not locked in by a static transform.
Protect the value, not just the copy
Sensitive values can stay encrypted, tokenized, or format-preserving at rest, so de-identification becomes real data protection instead of a one-time scrub that leaves the source exposed.
Identity-based reveal
At runtime the same protected value resolves to either the unprotected value or a configured protected representation, such as a masked, tokenized, encrypted, or format-preserving protected value, based on the requesting identity, application, service account, API, or workflow.
Traditional de-identification protects a copy once. Ubiq protects the value itself, then returns the right protected or unprotected version at runtime.
How Ubiq de-identifies sensitive data
Ubiq applies the right method for each field, such as masking, tokenization, or format-preserving protection, and returns a protected representation at runtime based on identity and policy.
| Type | Original value | Method | Protected value (output) | Runtime outcome |
|---|---|---|---|---|
| Name | Maria Chen | Mask | M•••• C••• | Cleartext hiddenOnly the masked form is returned |
| SSN | 555-12-1234 | Tokenize / protect | 7C2A-9F4B-D108 | Protected representationTokenized, not the raw identifier |
| Employee ID | EMP-3X9Q-1182 | Format-preserving protect | EMP-7K2M-4830 | Protected representationFormat preserved for compatibility |
| mariac@acme.com | Mask | m••••@acme.com | Partially revealed under policyMasked unless policy authorizes full |
Cleartext hidden:Only the masked form is returned
Protected representation:Tokenized, not the raw identifier
Protected representation:Format preserved for compatibility
Partially revealed under policy:Masked unless policy authorizes full
Traditional de-identification protects a copy once. Ubiq protects the value itself, then returns the right protected or unprotected version at runtime based on identity, context, and policy.
What data de-identification does not solve
De-identification reduces the link between data and a person, but as a static, one-way transform it still leaves real gaps. The trade-off between utility and re-identification risk is locked in once, and every consumer receives the same version regardless of who they are.
Re-identification risk remains
Generalized or partially masked datasets can often be re-identified by combining quasi-identifiers, especially at scale or against external data.
One-way transforms trade utility for safety
Strip too much and the data loses analytic value, strip too little and it stays re-identifiable. A static transform forces that trade-off once, for every consumer.
Static copies drift from the source
De-identified extracts are snapshots. They go stale, multiply across environments, and are governed separately from the production data they came from.
Access is treated as all or nothing
A de-identified dataset returns the same version to everyone, regardless of the role, context, or policy behind each request.
Ubiq protects the value itself, then returns the right protected or unprotected version at runtime based on identity, context, and policy.
How Ubiq works
Same sensitive data. Different identities. Different runtime outcomes.
Data de-identification protects the value. Ubiq evaluates the requesting identity, context, and policy at runtime, then returns either the unprotected value or a configured protected representation that identity is authorized to receive.
Access request
Protected employee record
- Employee ID
- EMP-3X9Q-1182
- Name
- Maria Chen
- maria@acme.com
- Salary
- $142,800
Real-time evaluation
Runtime data outcome
HR app
CleartextAuthorized to process the full employee record
Support analyst
MaskedNeeds to confirm the record, not read all fields
Analytics API
TokenizedAuthorized for analysis without exposing original identifiers
AI agent
EncryptedOperates on ciphertext, never cleartext
Protected once. Resolved differently at runtime for each identity.
Where teams use data de-identification
De-identification lets teams use sensitive data without exposing who it belongs to. These are the workflows where it matters most.
Analytics and BI
Give analysts and dashboards de-identified production data so they can work with real distributions without unrestricted access to raw identifiers.
AI, RAG, and model training
Train and query on de-identified data while sensitive source fields stay protected and identity-governed, limiting plaintext exposure across prompts, vector stores, and agents.
Secondary use and data sharing
Share datasets with partners, vendors, and researchers without exposing regulated identifiers, while keeping a governed path back to the original under policy.
Dev, test, and lower environments
Provision realistic de-identified data to development, QA, and vendor workflows without copying regulated values into less-protected systems.
Regulatory scope reduction
De-identify PII and PHI to reduce the scope of regulated data under frameworks like HIPAA, GDPR, and CCPA, while retaining a controlled way to re-link when authorized.
Insider threat and overprivileged access
Limit what broad DBA, admin, and service-account access can actually reveal by controlling which identities can re-identify sensitive fields.
Ubiq is built to fit your environment
Ubiq deploys inside your own environment and integrates where sensitive data already lives, so teams adopt it without heavy operational friction.
SDKs and APIs
Add protection with a few lines of code across major languages, live in minutes.
Database and warehouse integration
Protect and reveal values through SQL UDFs and native database and data warehouse integrations.
Application and API patterns
Integrate at applications, services, and API gateways without rearchitecting them.
Identity provider integration
Reuse your existing IAM so runtime decisions follow the identities you already manage.
Customer-managed keys
Bring your own HSM or KMS so key control stays with your team.
No agents, proxies, or schema changes
Deploy with no proxies in the data path and no database schema changes where applicable.
Frequently asked questions
What is data de-identification?
Data de-identification removes or transforms the identifiers that link a record to a specific person, so the data can be used for analytics, testing, AI, and sharing without revealing who it belongs to. Techniques include masking, tokenization, pseudonymization, generalization, and redaction.
What is the difference between de-identification, anonymization, and pseudonymization?
De-identification is the broad practice of reducing the link between data and a person. Anonymization generally refers to making that link as hard as possible to reverse, while pseudonymization replaces identifiers with values that can be re-linked under policy. Ubiq's model is governed, reversible protection: it returns the unprotected value when policy allows, or a configured protected representation when policy requires it, and governs who can re-identify a value at runtime.
How is Ubiq different from traditional data de-identification?
Traditional de-identification is a one-way batch transform applied once for every consumer, which forces a trade-off between data utility and re-identification risk. Ubiq protects the value itself with encryption, tokenization, or format-preserving protection, then returns either the unprotected value or a configured protected representation each identity is authorized to receive at runtime.
Does de-identified data eliminate re-identification risk?
Not on its own. Generalized or partially masked datasets can often be re-identified by combining quasi-identifiers, especially at scale. Ubiq reduces this risk by protecting the underlying value and governing re-identification by identity, context, and policy, instead of relying on a static transform that everyone receives the same way.
What runtime outcomes can Ubiq return for a de-identified field?
Based on identity and policy, Ubiq returns either the unprotected value or a configured protected representation, such as a masked value, tokenized value, encrypted value, format-preserving protected value, or another supported protected representation. This enforces least privilege at the level of the data value, not just the system.
Can Ubiq apply de-identification across databases, applications, and AI workflows?
Yes. Ubiq integrates through SDKs and APIs, SQL UDFs, and database and data warehouse integrations, so identity-governed de-identification applies consistently across applications, APIs, databases, warehouses, BI tools, and AI workflows.
How does Ubiq support HIPAA, GDPR, and CCPA de-identification?
Ubiq helps reduce the scope of regulated data by de-identifying PII and PHI while keeping a governed, policy-controlled path to re-identify when an authorized identity requires it. Because protection stays with the value and access is decided at runtime, teams can support analytics and sharing without broadly exposing regulated identifiers.
Can teams use de-identification for AI and RAG without exposing sensitive data?
Ubiq separates protection of sensitive source data from AI and vector computation. Sensitive records and identifiers stay protected and identity-governed, while AI, retrieval, and agent workflows use approved representations and policy-controlled access paths.