# Djinn Fake production data for ML. Source: [Console review]() Website: [https://djinn.tonic.ai/?signup]() Profile updated: 2026-10-16 Category: [Models & infrastructure]() ## Supported tech stack Research checked: 2026-10-11 Compatibility could not be verified. The listed product site and Djinn documentation could not be retrieved. Tonic's current documentation describes other products; their SDKs cannot establish Djinn support. ## Console’s review — 2023-03-02 Reviewed: 2023-03-02 Author: [David Mytton]() Citation: [This review]() ### What we like Enables privacy compliant training of ML models on realistic fake data. Connects to your prod database via SQL, transforms (fakes) the data, then trains your model. Provides a report after training to confirm how realistic the trained data was. Supports tabular and event driven models. Export to ipynb. Cloud or self-hosted. ### Tradeoffs No dark mode. Pretty hefty minimum requirements for self-hosting, but ML training is compute & GPU intensive. This review reflects Console’s assessment at publication on 2023-03-02. Features and limitations may have changed since the review date. ## Is Djinn a fit? Based on [Console’s review published on 2023-03-02](). Summary updated: 2026-10-16 ### Who it’s for Developers training machine learning models ### Why consider it Enables privacy compliant training of ML models on realistic fake data ### Keep in mind Has hefty minimum requirements for self-hosting [Selection criteria]() · [About Console]() · [Browse tools]()