Delivered·Dashboards & intelligence ·SaaS & software·canada

Confidential engagement

Synthetic data generation and privacy-preserving data pipeline for software development and testing, creating realistic test datasets from production schemas while maintaining privacy compliance (GDPR, HIPAA), and enabling safe data sharing across teams.

Next.jsTypeScriptPython for data generation (pandas, Faker, diffprivlib)LLM-based generation (GPT fine-tuning, data augmentation)Supabase for metadata and lineage trackingDocker containers for reproducible generation

Confidential engagement · canada

What we built

01Automated production data schema analysis

02Statistical distribution preservation (variance, correlations)

03Differential privacy implementation (epsilon tuning)

04Generative AI-based synthetic record generation (LLMs, GANs)

05Data quality validation (schema compliance, statistical tests)

06Test data versioning and reproducibility

07PII redaction and masking workflows

08CI/CD pipeline integration for automated test data

Technical stack