DataMasque
Category: AI Infrastructure
DataMasque is a data de-identification and synthetic data platform that automatically discovers and masks sensitive data, replacing it with synthetically identical customer data for development, testing, analytics, and AI. DataMasque was founded in 2021. The company is led by Grant de Leeuw. Based in Auckland, New Zealand. Team size: 11-50. Total funding raised: $7M. Latest round: Series A. Key investors include Wavemaker Partners, OIF Ventures, Icehouse Ventures.
- Founded
- 2021
- Headquarters
- Auckland, New Zealand
- Team size
- 11-50
- Total funding
- $7M
Value proposition
DataMasque enables enterprises to safely use sensitive customer data for AI training, testing, and analytics by automatically discovering and replacing sensitive information with synthetically identical data that looks and behaves like real data — removing the compromise between data quality and security.
Products and solutions
Data Discovery & Classification, Automated Data Masking, Synthetic Data Generation, Unstructured Data De-identification (call transcripts, emails, logs), API-first architecture with CI/CD integration, AWS-native deployment via AWS Marketplace, Cohesity integration
Unique value
Synthetically identical customer data — high-fidelity masking that preserves data utility, referential integrity, and edge cases while ensuring irreversible de-identification and compliance with GDPR, CCPA, HIPAA, and APRA standards.
Target customer
Enterprise organizations and government agencies in highly regulated industries (financial services, insurance, healthcare, government, telecommunications) that need to use sensitive customer data for development, testing, analytics, and AI/ML without compromising privacy or compliance.
Industries served
Financial Services/BFSI, Insurance, Healthcare, Government (NZ, Australia, US), Telecommunications, Hospitality
Technology advantage
SHA-512 salted hash irreversible masking; automated referential integrity preservation across tables/databases; sensitive data discovery using metadata keyword search and pattern matching; dark-site deployment (on-prem or private cloud); unified structured + unstructured data masking; AWS Strategic Collaboration Agreement partner with AWS Security Competency and Financial Services Competency
How they differentiate
Unlike traditional data masking tools that prioritize security at the expense of data usability, DataMasque generates "synthetically identical" data that preserves relationships, edge cases, and statistical properties across databases. It masks data 7x faster than traditional workflows (days to hours), supports dark-site deployment (data never leaves customer infrastructure), and offers a unified platform for both structured and unstructured data (call transcripts, emails, logs). The company has also secured a Strategic Collaboration Agreement with AWS.
Main competitors
Delphix (Perforce), Informatica, IBM InfoSphere Optim
Key partnerships
AWS (Strategic Collaboration Agreement signed Oct 2025, AWS Security Competency, AWS Financial Services Competency, APJ Rising Star Partner of the Year 2023), Cohesity
Notable customers
New York Life, ADP, Best Western Hotels & Resorts, One NZ, TAL, Tellihealth, Resolution Life, JLL, New Zealand government agencies, Victorian state government (Australia), US government agencies
Major milestones
2021: Company founded in Auckland, New Zealand, 2023: Named AWS APJ Rising Star Partner of the Year, 2023: Raised NZ$2.7M seed round led by OIF Ventures and Icehouse Ventures, 2025: Signed Strategic Collaboration Agreement with AWS, 2026: Raised US$4M Series A led by Wavemaker Partners, 2026: Launched unstructured data de-identification capability, 2026: Appointed Instaclustr co-founder Peter Lilley to board, 2026: Achieved 6x ARR growth and tripled headcount since 2023 seed round
Growth metrics
6x ARR growth since late 2023 seed round; tripled headcount (13 to ~25-30); North America now ~70% of revenue; 95%+ of revenue from production deployments (not pilots)
Market positioning
DataMasque positions itself as a next-gen data masking and synthetic data platform focused on preserving data utility (synthetically identical data) while ensuring compliance. It differentiates from incumbents by maintaining referential integrity, supporting both structured and unstructured data, and offering dark-site deployment within customer infrastructure. The company targets regulated enterprises in BFSI, government, healthcare, and telecom.
Geographic focus
Global (North America ~70% of revenue, Australia, New Zealand, India expanding)
About Grant de Leeuw
Over 20 years of international experience in leadership, product, sales and company director roles across technology, data and telecommunications. Holds a Business Studies Degree from Massey University.
Official website: https://www.datamasque.com