# Best Data De-Identification Tools

  *By [Brandon Summers-Miller](https://research.g2.com/insights/author/brandon-summers-miller)*

   Data de-identification tools help companies derive value from their datasets without the risks of using personally identifiable information. Data de-identification software remove sensitive or personally identifying data—names, dates of birth, and other identifiers—in datasets in a way that is not re-identifiable. Data de-identification solutions help companies derive value from datasets without compromising the privacy of the data subjects in a given dataset. Data de-identification is essential for companies working with sensitive and highly-regulated data. Companies choose to de-identify their data to reduce their risk of holding personally identifiable information and comply with privacy and data protection laws such as HIPAA, CCPA, and GDPR.

Data de-identification solutions has some overlap with [data masking software](https://www.g2.com/categories/data-masking), or data obfuscation software. However, with data de-identification solutions, the risk of the data being reidentified is low. With data masking, sensitive data retains its actual identifying features like age range and zip code but masks (or redacts blanks or hashes) identifying information such as names, addresses, phone numbers, and other sensitive data. It is possible to remove the data mask and re-identify the data. Data masking is often used as a way for companies to maintain sensitive data while preventing misuse of that data by employees or insider threats.

To qualify for inclusion in the Data De-identification category, a product must:

- Remove sensitive or identifying information from data
- Prevent re-identification of data
- Meet de-identification requirements under data privacy or data protection laws





## Category Overview

**Total Products under this Category:** 91


## Trust & Credibility Stats

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 800+ Authentic Reviews
- 91+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.


## Best Data De-Identification Tools At A Glance

- **Leader:** [Tonic.ai](https://www.g2.com/products/tonic-ai/reviews)
- **Highest Performer:** [Tumult Analytics](https://www.g2.com/products/tumult-analytics/reviews)
- **Easiest to Use:** [VGS Platform](https://www.g2.com/products/very-good-security-vgs-platform/reviews)
- **Top Trending:** [Tonic.ai](https://www.g2.com/products/tonic-ai/reviews)
- **Best Free Software:** [VGS Platform](https://www.g2.com/products/very-good-security-vgs-platform/reviews)


## Top-Rated Products (Ranked by G2 Score)
  ### 1. [IBM InfoSphere Optim Data Privacy](https://www.g2.com/products/ibm-infosphere-optim-data-privacy/reviews)
  IBM InfoSphere Optim Data Privacy protects privacy and support compliance using extensive capabilities to de-identify sensitive information across applications, databases and operating systems


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 47

**User Satisfaction Scores:**

- **Ease of Use:** 8.9/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.8/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 9.4/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.6/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Education Management
  - **Company Size:** 50% Mid-Market, 29% Small-Business


  ### 2. [Tumult Analytics](https://www.g2.com/products/tumult-analytics/reviews)
  Tumult Analytics is an advanced, open-source Python library designed to facilitate the deployment of differential privacy in data analysis. It enables organizations to generate statistical summaries from sensitive datasets while ensuring individual privacy is maintained. Trusted by institutions such as the U.S. Census Bureau, the Wikimedia Foundation, and the Internal Revenue Service, Tumult Analytics offers a robust and scalable solution for privacy-preserving data analysis. Key Features and Functionality: - Robust and Production-Ready: Developed and maintained by a team of differential privacy experts, Tumult Analytics is built for production environments and has been implemented by major institutions. - Scalable: Operating on Apache Spark, it efficiently processes datasets containing billions of rows, making it suitable for large-scale data analysis tasks. - User-Friendly APIs: The platform provides Python APIs that are familiar to users of Pandas and PySpark, facilitating easy adoption and integration into existing workflows. - Comprehensive Functionality: It supports a wide array of aggregation functions, data transformation operators, and privacy definitions, allowing for flexible and powerful data analysis under multiple privacy models. Primary Value and Problem Solved: Tumult Analytics addresses the critical challenge of extracting valuable insights from sensitive data without compromising individual privacy. By implementing differential privacy, it ensures that the risk of re-identification is minimized, enabling organizations to share and analyze data responsibly. This capability is particularly vital for sectors handling sensitive information, such as public institutions, healthcare, and finance, where maintaining data privacy is both a regulatory requirement and an ethical obligation.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 38

**User Satisfaction Scores:**

- **Ease of Use:** 8.6/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.8/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.5/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Tumult Labs, Inc.](https://www.g2.com/sellers/tumult-labs-inc)
- **Year Founded:** 2019
- **HQ Location:** Durham
- **LinkedIn® Page:** https://www.linkedin.com/company/tmltlabs (3 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 50% Small-Business, 32% Mid-Market


  ### 3. [Nymiz](https://www.g2.com/products/nymiz/reviews)
  AI-Driven Data Anonymization For Knowledge Management -\> Nymiz detects sensitive data in unstructured files (doc, docx, xls, xlsx, jpg, tlf, png, pdf) and also in structured data (databases), and anonymizes or pseudonymizes them reversibly or irreversibly. -\> By recognizing context-specific data like names, phone numbers, and social security numbers, Nymiz achieve superior results compared to tools that lack artificial intelligence capabilities. -\> Additional security layer at the data level. Anonymized or pseudonymized information has no practical value if it is stolen through a security breach or exposed by human errors. -\> Nymiz can read data in 102 languages besides English and Spanish. -\> Nymiz enables compliance with regulatory requirements regarding privacy and data protection for various frameworks: GDPR, CCPA, LOGPD & more. Our team specializes in designing bespoke data anonymization solutions to meet the unique requirements of your organization -\> Cloud-based solution (SaaS) -\> API Integration -\> On-premise solution -\> IT consulting and management services


  **Average Rating:** 5.0/5.0
  **Total Reviews:** 14

**User Satisfaction Scores:**

- **Ease of Use:** 10.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 10.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 10.0/10 (Category avg: 9.0/10)
- **CCPA compliant:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Nymiz](https://www.g2.com/sellers/nymiz)
- **Year Founded:** 2019
- **HQ Location:** Bilbao, ES
- **Twitter:** @nymizglobal (192 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/nymiz/ (37 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 57% Small-Business, 21% Enterprise


  ### 4. [Tonic.ai](https://www.g2.com/products/tonic-ai/reviews)
  Tonic.ai frees developers to build with safe, high-fidelity synthetic data to accelerate software and AI innovation while protecting data privacy. Through industry-leading solutions for data synthesis, de-identification, and subsetting, our products enable on-demand access to realistic structured, semi-structured, and unstructured data for software development, testing, and AI model training. The product suite includes: - Tonic Fabricate for AI-powered synthetic data from scratch - Tonic Structural for modern test data management - Tonic Textual for unstructured data redaction and synthesis. Unblock innovation, eliminate collisions in testing, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy. Founded in 2018, with offices in San Francisco, Atlanta, New York, and London, the company is pioneering enterprise tools for data synthesis and de-identification in pursuit of its mission to unblock innovation with usable data. Thousands of developers use data generated with the Tonic.ai platform on a daily basis to build products and train models faster in industries as wide ranging as healthcare, financial services, insurance, logistics, edtech, and e-commerce. Working with customers like Comcast, eBay, UnitedHealthcare, and Fidelity Investments, Tonic.ai builds developer solutions to advance its goals of advocating for the privacy of individuals while enabling companies to do their best work. Be free to build with high-fidelity synthetic data for software and AI development.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 38

**User Satisfaction Scores:**

- **Ease of Use:** 8.1/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.3/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Tonic.ai](https://www.g2.com/sellers/tonic-ai)
- **Company Website:** https://www.tonic.ai/
- **Year Founded:** 2018
- **HQ Location:** San Francisco, California
- **Twitter:** @tonicfakedata (699 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/18621512 (100 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Financial Services
  - **Company Size:** 45% Mid-Market, 32% Small-Business


  ### 5. [VGS Platform](https://www.g2.com/products/very-good-security-vgs-platform/reviews)
  Very Good Security (“VGS”) makes it easy for customers to collect, protect and share sensitive financial data in a way that accelerates revenue, eliminates risk, ensures compliance, and drives profitability. VGS secures that information in an encrypted token vault; enabling our customers to de-risk their technical environment and achieve compliance certifications like PCI DSS, SOC 2, GDPR, and more, faster. VGS delivers a modern solution to collect, protect, and exchange sensitive data that spans from data privacy to payment acceptance and card issuance; providing businesses with tokenization, PCI compliance, data security, processor optionality, and the ability to operate on that data without compromising their security posture. VGS delivers a modern payments security solution that gives businesses ownership and control over critically valuable customer data, granting them maximum portability, operationality, and value extraction. VGS customers decouple the value and utility of data from the associated security and compliance risks and allow customers to achieve continuous PCI DSS compliance 16x faster, at 25% the cost of a DIY approach.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 46

**User Satisfaction Scores:**

- **Ease of Use:** 9.4/10 (Category avg: 8.9/10)
- **GDPR compliant:** 10.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.3/10 (Category avg: 9.0/10)
- **CCPA compliant:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Very Good Security](https://www.g2.com/sellers/very-good-security)
- **Year Founded:** 2015
- **HQ Location:** San Francisco, California
- **Twitter:** @getvgs (1,430 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/18142614/ (452 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer
  - **Top Industries:** Financial Services, Banking
  - **Company Size:** 51% Mid-Market, 45% Small-Business


  ### 6. [Informatica Data Security Cloud](https://www.g2.com/products/informatica-data-security-cloud/reviews)
  Informatica Data Security Cloud is a comprehensive solution designed to protect sensitive and private data, enhance compliance, and enforce data usage policies without requiring changes to existing applications. By leveraging advanced data masking and anonymization techniques, it ensures that critical information remains secure across various environments, including testing, development, analytics, and customer experience programs. This cloud-native service integrates seamlessly with Informatica's Intelligent Data Management Cloud, providing a holistic approach to data governance and privacy. Key Features and Functionality: - Cloud Data Masking: De-identifies and anonymizes sensitive data to prevent unauthorized access, supporting compliance and data security initiatives. - High-Performance Data Masking: Centrally manages and scales masking processes for large data volumes across diverse data stores and locations. - Robust Data Masking and Encryption: Utilizes various techniques such as substitution, format-preserving encryption (FPE, blurring, sequential, and randomization to protect data. - Broad Connectivity and Custom Application Support: Supports data masking across multiple formats and a wide range of databases, mainframes, and applications. - Automated Data Discovery: Identifies sensitive data locations quickly, ensuring consistent masking across databases. - Self-Service Data Warehouse: Stores, augments, shares, and reuses test datasets to improve testers’ efficiency. - Data Subset: Provisions smaller datasets to minimize infrastructure requirements and enhance performance. - Monitoring and Reporting: Engages risk, compliance, and audit teams to align with data governance initiatives. Primary Value and User Solutions: Informatica Data Security Cloud addresses the critical need for organizations to protect sensitive data while maintaining operational efficiency. By anonymizing and de-sensitizing data, it reduces the risk of data breaches and ensures compliance with data privacy regulations. The solution's ability to manage and scale data masking processes across various environments allows businesses to securely utilize data in testing, development, analytics, and customer experience initiatives without compromising data integrity or security. This empowers organizations to confidently share and use data, fostering innovation and informed decision-making.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 45

**User Satisfaction Scores:**

- **Ease of Use:** 8.1/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.3/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.7/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Informatica](https://www.g2.com/sellers/informatica)
- **Year Founded:** 1993
- **HQ Location:** Redwood City, CA
- **Twitter:** @Informatica (99,880 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3858/ (5,337 employees on LinkedIn®)
- **Ownership:** NYSE: INFA

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Computer & Network Security
  - **Company Size:** 40% Enterprise, 33% Small-Business


  ### 7. [brighter AI](https://www.g2.com/products/brighter-ai/reviews)
  Protect identities. Preserve data quality. Innovate faster. brighter AI provides the world’s most advanced image and video anonymization software. We help organizations turn personal data into compliant, usable assets for analytics and machine learning. Our deep learning solutions ensure full compliance with GDPR, CCPA, and APPI by protecting identities in public spaces—all without compromising the data quality needed for video analytics. Privacy and performance, combined.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 23

**User Satisfaction Scores:**

- **Ease of Use:** 8.9/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.3/10 (Category avg: 9.2/10)
- **CCPA compliant:** 9.7/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [BrighterAi](https://www.g2.com/sellers/brighterai)
- **Year Founded:** 2017
- **HQ Location:** Berlin, Germany
- **Twitter:** @brighterAI (636 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/18144227 (30 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 48% Small-Business, 26% Mid-Market


#### Pros & Cons

**Pros:**

- AI Technology (1 reviews)
- Data Privacy (1 reviews)
- Ease of Setup (1 reviews)
- Quality Control (1 reviews)

**Cons:**

- Complexity (1 reviews)
- Lack of Guidance (1 reviews)
- Not User-Friendly (1 reviews)

  ### 8. [Limina](https://www.g2.com/products/limina/reviews)
  Limina is an enterprise de-identification platform that detects and removes PII, PHI, and PCI from unstructured data without stripping the context that makes it valuable. Unlike pattern-matching tools that over-redact, Limina uses context-aware machine learning to identify sensitive information the way a trained human would. That's why it achieves less than half the error rate of AWS Comprehend, Google DLP, and Microsoft Presidio on real-world data. What Limina Detects 50+ entity types across PII, PHI, and PCI — names, SSNs, credit card numbers, medical conditions, medications, passport numbers, and international variants — across 52 languages including English, French, German, Spanish, Japanese, and Mandarin. How It's Deployed Limina deploys as a self-hosted container via REST API. Your data is processed entirely within your own infrastructure—never transmitted to Limina or any third party. Available as a CPU version for standard deployments or a GPU version for real-time and high-throughput workloads. Synthetic Data Generation Limina can replace detected PII with synthetic data that fits the surrounding context, preserving the statistical and linguistic integrity of your dataset for downstream AI training, analytics, and partner sharing. Limina's models are built and maintained by a team of linguists, data annotators, and privacy experts, and updated continuously to reflect evolving global privacy regulations. Get Started Try the text demo: https://docs.getlimina.ai/demo/text Try the file demo: https://docs.getlimina.ai/demo/file Get a free API key: https://portal.getlimina.ai/


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 21

**User Satisfaction Scores:**

- **Ease of Use:** 9.4/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.2/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.9/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.6/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Limina](https://www.g2.com/sellers/limina)
- **Year Founded:** 2019
- **HQ Location:** Toronto, CA
- **Twitter:** @PrivateAI (1 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/private-ai (168 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 36% Mid-Market, 36% Small-Business


  ### 9. [Informatica Dynamic Data Masking](https://www.g2.com/products/informatica-dynamic-data-masking/reviews)
  Data security and privacy for data in use by both mission-critical and line-of-business applications.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 20

**User Satisfaction Scores:**

- **Ease of Use:** 8.6/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.3/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 7.9/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.6/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Informatica](https://www.g2.com/sellers/informatica)
- **Year Founded:** 1993
- **HQ Location:** Redwood City, CA
- **Twitter:** @Informatica (99,880 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3858/ (5,337 employees on LinkedIn®)
- **Ownership:** NYSE: INFA

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 50% Enterprise, 27% Small-Business


  ### 10. [Evervault](https://www.g2.com/products/evervault-2022-11-22/reviews)
  Evervault is a developer-first platform that helps payment providers and merchants collect, process, and share sensitive cardholder data without ever exposing it in plaintext. Its modular building blocks are designed to solve payment security, PCI compliance, and data protection challenges with minimal engineering effort. The platform uses a dual-custody encryption model: Evervault stores the encryption keys, while customers store the encrypted data. This separation drastically reduces breach risk and improves performance. Developers can encrypt data at the point of collection and keep it encrypted throughout its lifecycle using simple SDKs and APIs. For payments, Evervault tokenizes card details on capture, keeping merchants out of PCI DSS scope. These tokens can be sent to any PSP, offering flexibility in routing and simplifying compliance. Evervault also offers standalone products, such as 3D Secure and Network Tokens, providing teams with more control over authentication flows and payment optimization.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 17

**User Satisfaction Scores:**

- **Ease of Use:** 9.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 9.2/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.9/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Evervault](https://www.g2.com/sellers/evervault-db9d562a-5ceb-48d9-853a-0ed902b2b5e1)
- **Year Founded:** 2019
- **HQ Location:** Dublin, IE
- **Twitter:** @evervault (3,239 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/evervault/ (27 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 59% Small-Business, 29% Mid-Market


  ### 11. [Privacy Vault](https://www.g2.com/products/privacy-vault/reviews)
  PRIVACY VAULT is intended to support industries that collect and process personal profiles, high-velocity consumer activity and IoT data, plus unstructured documents, images, voice and video.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 20

**User Satisfaction Scores:**

- **Ease of Use:** 8.6/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.3/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [ContextSpace](https://www.g2.com/sellers/contextspace)
- **Year Founded:** 2015
- **HQ Location:** Petach Tikvah, Israel
- **LinkedIn® Page:** https://www.linkedin.com/company/51621389 (1 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 48% Small-Business, 38% Enterprise


  ### 12. [Privacy1](https://www.g2.com/products/privacy1/reviews)
  Privacy1 is a software company in Stockholm and London that develops technologies for practical management of personal data. Our mission is to be an enabler to make data protection easier and accessible to all sizes of business and organisations. Our zero trust privacy solution allow you to secure protect the actual personal data in your environment that helps you prevent breach and control data flows to cross border processors. Our GDPR compliance suite provides all the components that businesses need as standard including data mapping, Pre DPIA, Full Impact assessment, Cookie Management, Privacy Policy management and Governance. Our Privacy Navigator is unique and will help you identify risks, compliance gaps and holes in your privacy stance across the business, it gives you a plan to resolve them and a platform to iteratively improve maturity and show accountability, even if you are not a GDPR expert. With a vision to provide solutions to help companies and governments protect personal data, manage their compliance and demonstrate accountability to ensure they can fulfil their privacy promises and meet regulatory obligations. Privacy1 is about building trust through better data privacy practises and technology for the advantage of all.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 87

**User Satisfaction Scores:**

- **Ease of Use:** 8.6/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.8/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.6/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Privacy1](https://www.g2.com/sellers/privacy1)
- **Year Founded:** 2018
- **HQ Location:** Stockholm, SE
- **LinkedIn® Page:** https://www.linkedin.com/company/35437546 (2 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 38% Small-Business, 34% Mid-Market


  ### 13. [Kiprotect](https://www.g2.com/products/kiprotect/reviews)
  KIProtect makes it easy to ensure compliance and security when working with sensitive or personal data.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 22

**User Satisfaction Scores:**

- **Ease of Use:** 9.1/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.2/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Kiprotect](https://www.g2.com/sellers/kiprotect)
- **Year Founded:** 2018
- **HQ Location:** Berlin, DE
- **LinkedIn® Page:** https://www.linkedin.com/company/11751103 (2 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 43% Small-Business, 39% Mid-Market


  ### 14. [Mage Privacy Enhancing Technologies](https://www.g2.com/products/mage-privacy-enhancing-technologies/reviews)
  Sensitive Data Discovery, Data Masking. Access Controls.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 20

**User Satisfaction Scores:**

- **Ease of Use:** 8.1/10 (Category avg: 8.9/10)
- **GDPR compliant:** 7.5/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 7.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Mage](https://www.g2.com/sellers/mage-9e06db3d-e432-4799-9fcf-e9d9c898f1dd)
- **Year Founded:** 2014
- **HQ Location:** New York, NY
- **LinkedIn® Page:** https://www.linkedin.com/company/217968 (84 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 60% Small-Business, 30% Mid-Market


  ### 15. [Aircloak Insights](https://www.g2.com/products/aircloak-insights/reviews)
  Aircloak enables organisations to gain flexible and secure insights into sensitive data sets through a smart, automatic, on-demand anonymization engine. It ensures compliance for both internal analysts and external partners or customers.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 11

**User Satisfaction Scores:**

- **Ease of Use:** 8.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.3/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 7.0/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Aircloak](https://www.g2.com/sellers/aircloak)
- **Year Founded:** 2012
- **HQ Location:** Berlin, Germany
- **Twitter:** @aircloak (463 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3543896 (1 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 45% Mid-Market, 27% Enterprise


  ### 16. [KIProtect Kodex](https://www.g2.com/products/kiprotect-kodex/reviews)
  Data anonymization is a type of information sanitization in order to protect privacy. It is the process of either encrypting or removing personally identifiable information from a data set so that the people whom the data describe remain anonymous.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 9

**User Satisfaction Scores:**

- **Ease of Use:** 8.5/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 7.5/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [KIProtect](https://www.g2.com/sellers/kiprotect-01623a8a-de09-4501-80da-42282e597c66)
- **Year Founded:** 2011
- **HQ Location:** Green Bay, WI
- **LinkedIn® Page:** https://www.linkedin.com/company/kidesignio/ (10 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 78% Mid-Market, 22% Small-Business


  ### 17. [BizDataX](https://www.g2.com/products/bizdatax/reviews)
  BizDataX makes data masking/data anonymization simple, by cloning production or extracting only a subset of data. And mask it on the way, achieving GDPR compliance easier.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 14

**User Satisfaction Scores:**

- **Ease of Use:** 7.9/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.4/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 10.0/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.2/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Span D.D.](https://www.g2.com/sellers/span-d-d)
- **Year Founded:** 1993
- **HQ Location:** N/A
- **LinkedIn® Page:** https://www.linkedin.com/company/span/ (998 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 50% Small-Business, 36% Enterprise


  ### 18. [PCI Vault](https://www.g2.com/products/pci-vault/reviews)
  PCI Vault is a vendor neutral, zero-knowledge, PCI DSS level 1 compliant environment by SnapBill, Inc. It is a SaaS solution offering credit card Tokenization as a Service (TaaS) combined with it's own Entropy as a Service (EaaS) engine for lightning quick enterprise grade encryption. Leveraging the Standard Unix Password Manager and PGP, this PCI Vault is open for use by anyone requiring a secure PCI compliant environment to store sensitive payment card data in any format.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 12

**User Satisfaction Scores:**

- **Ease of Use:** 9.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.8/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 7.9/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [SnapBill, Inc. DBA PCI Vault](https://www.g2.com/sellers/snapbill-inc-dba-pci-vault)
- **Year Founded:** 2008
- **HQ Location:** Wilmington, US
- **Twitter:** @pcicards
- **LinkedIn® Page:** https://www.linkedin.com/company/pcivault/ (1 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 42% Mid-Market, 33% Small-Business


#### Pros & Cons

**Pros:**

- Encryption (2 reviews)
- Security (2 reviews)
- Compliance (1 reviews)
- Ease of Use (1 reviews)
- Protection (1 reviews)

**Cons:**

- Slow Performance (2 reviews)
- Complexity Issues (1 reviews)
- Learning Difficulty (1 reviews)
- Update Issues (1 reviews)

  ### 19. [SecuPi Platform](https://www.g2.com/products/secupi-platform/reviews)
  SecuPi helps enterprises protect and take control of their data, ensuring it is discovered, monitored, governed, and secured in a compliant way. The SecuPi Data Security Platform gives organizations clarity into where sensitive data lives, who is accessing it, and how it is being used. By unifying discovery, monitoring, access control, and enforcement into one consistent approach, SecuPi embeds security directly into business applications, analytics, cloud platforms, and AI workloads, so data remains protected at every stage: in motion, in use, and at rest. Trusted by Fortune 500 companies across financial services, insurance, telecom, retail, and beyond, SecuPi helps security and compliance leaders reduce risk, simplify regulatory demands, and accelerate digital transformation with confidence.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 12

**User Satisfaction Scores:**

- **Ease of Use:** 8.1/10 (Category avg: 8.9/10)
- **GDPR compliant:** 6.7/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.3/10 (Category avg: 9.0/10)
- **CCPA compliant:** 5.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [SecuPi](https://www.g2.com/sellers/secupi)
- **Company Website:** https://www.secupi.com/
- **Year Founded:** 2014
- **HQ Location:** New York, US
- **Twitter:** @Secu_Pi (259 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/secupi (72 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 33% Enterprise, 25% Small-Business


#### Pros & Cons

**Pros:**

- Security (7 reviews)
- Data Protection (5 reviews)
- Data Security (3 reviews)
- Ease of Use (3 reviews)
- Easy Integrations (3 reviews)

**Cons:**

- Complexity (4 reviews)
- Improvement Needed (3 reviews)
- Integration Issues (3 reviews)
- Complexity Issues (2 reviews)
- Complexity Management (2 reviews)

  ### 20. [Baffle](https://www.g2.com/products/baffle/reviews)
  Baffle's solution goes beyond simple encryption to truly close gaps in the data access model. The technology protects against some of the most recent high profile attacks. It's easy to deploy, requires no changes to the apps, and encrypts data at-rest, in use, in memory and in the search index. That’s complete data protection.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 10

**User Satisfaction Scores:**

- **Ease of Use:** 9.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.9/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.3/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.4/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Baffle](https://www.g2.com/sellers/baffle)
- **Year Founded:** 2015
- **HQ Location:** Santa Clara
- **Twitter:** @baffleio (233 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/baffle-inc./about (31 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 55% Small-Business, 36% Mid-Market


  ### 21. [Anonomatic PII as a Service](https://www.g2.com/products/anonomatic-pii-as-a-service/reviews)
  Anonomatic PII Vault is a set of tools organizations may use to comply with local and international data privacy obligations while simultaneously utilizing the full value of their data. Accessible at three levels; API, Passthrough Anonymization or Privacy Pipelines data may be fully anonymized, masked or re-identified depending on the business needs and allowable functionality.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 6

**User Satisfaction Scores:**

- **Ease of Use:** 7.9/10 (Category avg: 8.9/10)
- **GDPR compliant:** 8.9/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 9.4/10 (Category avg: 9.0/10)
- **CCPA compliant:** 9.4/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Anonomatic](https://www.g2.com/sellers/anonomatic)
- **HQ Location:** San Francisco Bay Area, US
- **Twitter:** @AnonomaticInc (6 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/anonomatic/ (12 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 50% Small-Business, 33% Mid-Market


  ### 22. [Truata Calibrate](https://www.g2.com/products/truata-calibrate/reviews)
  Truata delivers privacy-enhanced data management and analytics solutions to help companies unlock business growth while protecting customer privacy. Truata was founded in 2018, with investment from Mastercard and IBM. We are based in Dublin, Ireland. We provide software for quantitative measurement of privacy risk in data sets within a company’s own data environment. This generates numerical risk scores based on inference, singling out and re-identification risks and provides recommendations on mitigation actions to ensure data is safe to use or share. The Truata Anonymization Service is a cutting-edge solution for GDPR-grade data anonymization & analytics, allowing companies to analyse and monetize customer data in fully-anonymized form.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 6

**User Satisfaction Scores:**

- **Ease of Use:** 8.9/10 (Category avg: 8.9/10)
- **GDPR compliant:** 10.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 10.0/10 (Category avg: 9.0/10)
- **CCPA compliant:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Truata](https://www.g2.com/sellers/truata)
- **HQ Location:** Leopardstown, IE
- **LinkedIn® Page:** https://www.linkedin.com/company/11529249 (42 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 50% Small-Business, 33% Mid-Market


  ### 23. [Anonyome Platform](https://www.g2.com/products/anonyome-platform/reviews)
  Sudo Platform is an API-first developer-focused ecosystem that delivers the tools necessary to empower our partners’ users and end consumers with the necessary capabilities to protect and control their personal information while navigating the digital world. It provides a modular, quickly implemented, and powerful collection of the most important digital privacy and safety tools including: Safe and private browsing (ad and tracker blocking, site reputation, and mobile private browsing) Cyber-safety (virtual cards, password management, and VPN) Open communications (email, voice, and SMS/MMS) Secure communications (encrypted individual and group email, voice, video, and messaging) Decentralized Identity (digital identity wallet, issuer services, verifier services, and more)


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 10

**User Satisfaction Scores:**

- **Ease of Use:** 9.5/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Anonyome Labs](https://www.g2.com/sellers/anonyome-labs)
- **Year Founded:** 2014
- **HQ Location:** Salt Lake City, US
- **Twitter:** @AnonyomeLabs (3,694 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/anonyome-labs-inc-/ (119 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Games
  - **Company Size:** 50% Mid-Market, 30% Enterprise


  ### 24. [AuricVault](https://www.g2.com/products/auricvault/reviews)
  AuricVault Tokenization is a payment processing software that associates tokens with secure encrypted data. It encrypts the data it receives and then stores the encrypted data along with a random set of characters.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 8

**User Satisfaction Scores:**

- **Ease of Use:** 9.0/10 (Category avg: 8.9/10)
- **GDPR compliant:** 10.0/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.9/10 (Category avg: 9.0/10)
- **CCPA compliant:** 8.9/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Auric Systems International](https://www.g2.com/sellers/auric-systems-international)
- **HQ Location:** N/A
- **Twitter:** @TokenEx (1,209 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 63% Small-Business, 25% Enterprise


  ### 25. [GrowthDot GDPR Compliance for Zendesk](https://www.g2.com/products/growthdot-gdpr-compliance-for-zendesk/reviews)
  GDPR Compliance for Zendesk is a powerful application designed to facilitate seamless compliance with Government Data Protection Regulations, particularly the stringent GDPR standards in Europe. This indispensable tool helps organizations manage and safeguard customer data with ease, ensuring compliance while optimizing Zendesk storage and streamlining data management processes. Key Features: - Effortless Data Management: Simplify compliance with GDPR regulations by easily handling customer data - whether it's deletion, anonymization, or downloading for client requests - all accomplished in just a few clicks. - Bulk Data Handling: Effortlessly remove users' or organizations' data, along with related tickets, directly from created tickets, contacts, or organization lists within Zendesk, or through CSV file uploads, streamlining data management tasks. - Anonymization of Sensitive Information: Ensure compliance with GDPR standards by anonymizing sensitive user information, including credit card numbers, allowing for lawful analysis of client preferences and issues while maintaining data confidentiality. - Comprehensive Data Retrieval & Compilation: Quickly gather customer data - including tickets and attachments - in bulk or individually. Export results into organized CSV files or compile everything into a single downloadable folder to easily fulfill compliance and client data requests. - Bulk Attachment Redaction & Storage Optimization: Free up valuable Zendesk storage space by redacting unnecessary attachments from tickets (individually or in bulk) without affecting other ticket data. Optimize storage usage and cut costs without upgrading your Zendesk plan. - Advanced Customization: Tailor the app to your organization’s needs by setting preferences for each GDPR process. From defining rules for anonymization to configuring how data is retrieved or deleted, customization ensures compliance matches your workflows. - Combined Lists for Specific Data Sets: Create combined lists that merge two data types (like users without tickets or tickets within organizations with a specific tag) to precisely target the records you need. This makes it faster and more efficient to run GDPR processes on very specific datasets. - Automation and Scheduling: Schedule GDPR processes to automatically delete or anonymize data as needed, saving time and ensuring ongoing compliance with regulations. - Real-time Reports and Easy Use: Generate real-time statistics and reports in multiple file formats. The intuitive interface makes it easy for any Zendesk agent to stay compliant without technical expertise. Why choose GDPR Compliance for Zendesk? With its easy-to-use interface, powerful bulk processing, advanced customization, and storage optimization, GDPR Compliance for Zendesk goes beyond standard compliance tools. It’s your all-in-one solution for managing sensitive data efficiently, reducing storage costs, and keeping your organization fully compliant.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 5

**User Satisfaction Scores:**

- **Ease of Use:** 8.3/10 (Category avg: 8.9/10)
- **GDPR compliant:** 9.6/10 (Category avg: 9.2/10)
- **Static pseudonymization:** 8.8/10 (Category avg: 9.0/10)
- **CCPA compliant:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [GrowthDot](https://www.g2.com/sellers/growthdot)
- **Year Founded:** 2016
- **HQ Location:** Ternopil, UA
- **Twitter:** @growthdot (294 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/growthdot-com/ (5 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 50% Small-Business, 33% Enterprise


#### Pros & Cons

**Pros:**

- Automation (2 reviews)
- Collaboration (1 reviews)
- Data Protection (1 reviews)
- Data Security (1 reviews)
- Ease of Use (1 reviews)

**Cons:**

- Learning Curve (2 reviews)
- Complex Integration (1 reviews)
- Complexity Issues (1 reviews)
- Data Management (1 reviews)
- Time-Consuming (1 reviews)



## Parent Category

[Data Privacy Software](https://www.g2.com/categories/data-privacy-3d79da1e-6384-42b3-a11f-d04b6694e806)



## Related Categories

- [Encryption Software](https://www.g2.com/categories/encryption-software)
- [Data Masking Software](https://www.g2.com/categories/data-masking)



---

## Buyer Guide

### What You Should Know About Data De-identification Tools

### What are Data De-Identification Tools?

Data de-identification tools remove direct and indirect sensitive data and personally-identifying information from datasets to reduce the reidentification of that data. Data de-identification is particularly important for companies working with sensitive and highly-regulated data, such as those in healthcare working with protected health information (PHI) in medical records or financial data. 

Companies may be prohibited from analyzing datasets that include sensitive and personally identifiable information (PII) in order to comply with internal policies and meet data privacy and data protection regulations. However, if the sensitive data is removed from a dataset in a non-identifiable manner, that dataset may become usable. For example, using data de-identification software tools, information such as peoples’ names, addresses, protected health information, tax identifying number, social security number, account numbers, and other personally identifying or sensitive data can be removed from datasets enabling companies to extract analytical value from the remaining de-identified data. 

When considering using de-identified datasets, companies should understand the risks of that sensitive data becoming re-identified. Reidentification risks can include differencing attacks, such as where bad actors use their knowledge about people to see if specific individuals’ personal data is included in a dataset, or reconstruction attacks, where someone combines data from other data sources to reconstruct the original de-identified dataset. When evaluating data de-identification methods, understanding the degree of anonymity using k-anonymity is important. 

### What are the Common Features of Data De-identification Tools?

The following are some core features within data de-identification tools:

**Anonymization:** Some data de-identification solutions offer statistical data anonymization methods, including k-anonymity, low-count suppression, and noise insertion. When working with sensitive data, particularly regulated data, anonymization weights and techniques to achieve that must be considered. The more anonymized the data is, the lesser the risk of re-identification. However, the more anonymous a dataset is made, the less its utility and accuracy. 

**Tokenization or pseudonymization:** Tokenization or pseudonymization replaces sensitive data with a token value stored outside the production dataset; it effectively de-identifies the dataset in use but can be reconstructed when needed.

### What are the Benefits of Data De-identification Tools?

The biggest benefit of using data de-identification tools is enabling analyses of data that would otherwise be prohibited from use. This allows companies to extract insights from their data while following data privacy and protection regulations by protecting sensitive information.

**Data usability for data analysis:** Enables companies to analyze datasets and extract value from datasets that would otherwise be unable to be processed due to the sensitivity of data contained within them. 

**Regulatory compliance:** Global data privacy and protection regulations require companies to treat sensitive data differently than non-sensitive data. If a dataset can be made non-sensitive using data de-identification software techniques, it may no longer be in the scope of data privacy or data protection regulations.

### Who Uses Data De-identification Tools?

Data de-identification solutions are used by people analyzing production data or those creating algorithms. De-identified data can also be used for safe data sharing.

**Data Managers, administrators, and data scientists:** These professionals who interact with datasets regularly will likely work with data de-identification software tools.

**Qualified experts:** These include qualified experts under HIPAA and can provide expert determination to attest that a dataset is deemed de-identified and the risks of re-identification are small based on generally accepted statistical methods.  

### What are the Alternatives to Data De-identification Tools?

Depending on the type of data protection a company is looking for, alternatives to data de-identification tools may be considered. For example, when determining when the data de-identification process is best, data masking may be a better option for companies that want to limit people from viewing sensitive data within applications. If the data merely needs to be protected during transit or at rest, encryption software may be a choice. If privacy-safe testing data is needed, synthetic data may be an alternative.

[Data masking software](https://www.g2.com/categories/data-masking): Data masking software obfuscates the data while retaining the original data. The mask can be lifted to reveal the original dataset. 

[Encryption software](https://www.g2.com/categories/encryption) **:** Encryption software protects data by converting plaintext into scrambled letters, known as ciphertext, which can only be decrypted using the appropriate encryption key. 

[Synthetic data software](https://www.g2.com/categories/synthetic-data): Synthetic data software helps companies create artificial datasets, including images, text, and other data from scratch using computer-generated imagery (CGI), generative neural networks (GANs), and heuristics. Synthetic data is most commonly used for testing and training machine learning models.

### Challenges with Data De-identification Tools

Software solutions can come with their own set of challenges. 

**Minimizing re-identification risks:** Simply removing personal information from a dataset may not be enough to consider the dataset de-identified. Indirect personal identifiers— contextual personal information within the data—may be used to re-identify a person in the data. Reidentification can happen from cross-referencing one dataset with another, singling out specific factors that relate to a known individual, or through general inferences of data that tend to correlate. De-identifying both direct and indirect identifiers, introducing noise (random data), and generalizing the data by reducing the granularity and analyzing it in aggregate can help prevent re-identification. 

**Meeting regulatory requirements:** Many data privacy and data protection laws do not specify technical requirements for what is considered de-identified or anonymous data, so it is up to companies to understand the technical capabilities of their software solutions and how that relates to adhering to data protection regulations.

### How to Buy Data De-identification Tools

#### Requirements Gathering (RFI/RFP) for Data De-identification Tools

Users must determine their specific needs for data de-identification tools. They can answer the questions below to get a better understanding:

- What is the business purpose of seeking data de-identification software? 
- What kind of data is the user trying to de-identify? 
- Would data masking, data encryption, or synthetic data be an alternative for their use cases? 
- What degree of anonymity is needed?
- Is it financial information, classified information, proprietary business information, personally identifiable information, or other sensitive data?
- Have they identified where those sensitive data stores are--on-premises or in the cloud?
- What specific software applications is that data used in? 
- What software integrations may be needed?
- Who within the company should be authorized to view sensitive data, and who should be served with the de-identified data? 

#### Compare Data De-identification Software Products

**Create a long list**

Buyers can visit G2’s [Data De-identification Software](https://www.g2.com/categories/data-de-identification-and-pseudonymity) category, read reviews about data de-identification products, and determine which products fit their businesses’ specific needs. They can then create a list of products that match those needs.

**Create a short list**

After creating a long list, buyers can review their choices and eliminate some products to create a shorter, more precise list.

**Conduct demos**

Once buyers have narrowed down their software search, they can connect with the vendor to view demonstrations of the software product and how it relates to their company’s specific use cases. They can ask about the de-identification methods. Buyers can also ask about integrations with their existing tech stack, licensing methods, and pricing—whether fees are based on the number of projects, databases, executions, etc.

#### Selection of Data De-identification Tools

**Choose a selection team**

Buyers must determine which team is responsible for implementing and managing this software. Often, that may be someone from the data team. It is important to have a representative from the financial team on the selection committee to ensure the license is within budget. 

**Negotiation**

Buyers should get specific answers to the license cost, how it is priced, and if the data de-identification software is based on the dataset size, features, or execution. They must keep in mind the company’s data de-identification needs for today and the future.

**Final decision**

The final decision will come down to whether the software solution meets the technical requirements, the usability, the implementation, other support, the expected return on investment, and more. Ideally, the data team will make the final decision, alongside input from other stakeholders like software development teams.