Question: I need a solution to generate realistic test data for my development team without compromising privacy or security.

If you need a way to generate realistic test data without privacy or security problems, Tonic is a good choice. This developer data solution speeds up engineering velocity and compliance by generating test data that's as complex as production. It can tap into a variety of data sources, including relational databases and data warehouses, and offers a pay-as-you-go pricing plan starting at $199/month. Tonic is used by engineering teams at eBay and Everlywell and helps teams deliver faster while protecting data privacy.

Another option is MOSTLY AI, a synthetic data generation platform from GenAI. The platform makes data generation accessible to anyone without programming skills and is designed for enterprise customers. It can generate anonymous synthetic data to meet privacy requirements and is certified for ISO27001 and SOC2 Type 2. MOSTLY AI is good for data sharing, AI/ML development, self-service analytics, and testing & QA. Pricing is flexible, including a free tier.

If you need AI-generated seed data for relational databases, Snaplet offers realistic data that's similar to what you'd see in production. It can generate seed data on the fly, check its types for safety and anonymize data so you can easily subset production databases for local development. Snaplet supports PostgreSQL, SQLite and MySQL, among other databases. Pricing includes a free tier and a $30/month pro plan.

If you need a more general-purpose data management and AI development foundation, take a look at Dataloop. The platform combines data curation, model management, pipeline orchestration and human feedback to speed up AI application development. Dataloop supports many types of unstructured data and has strong security controls that meet GDPR, ISO 27001 and SOC 2 Type II standards. It's designed to improve collaboration, speed up development time and maintain high quality and security.