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GitHub - rapiddweller/datamimic: Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments.

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DATAMIMIC — Governed Test Data for Regulated Enterprises This repository contains the DATAMIMIC Community Edition (CE). MIT-licensed, Python-native, MCP-ready. CE is fully usable standalone for deterministic synthetic data generation and PII-aware pseudonymization. The Enterprise Platform adds governed workflows, PII scanning, role-based access, audit logging, scheduling, multi-system execution, and the full operational layer that regulated enterprises require. 👉 Enterprise Platform: datamimic.io  |  📘 Docs: docs.datamimic.io  |  📅 Book a strategy call: datamimic.io/contact 🤖 AI agent? Start at AGENTS.md and use the project CLI: preserve new intent as model.dm.json , submit an early best attempt via datamimic scaffold ... --format json , repair from the structured issues, declare an expectation per stated requirement, and stop on verified=true . Existing raw XML uses lint plus bounded dry-run. What is DATAMIMIC?…

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