Creating training datasets is often harder than training models. Synthetic Data Factory helps you generate realistic, structured synthetic datasets for ML tasks like NER, OCR, and fine-tuning, especially when real datasets don’t exist. Describe the scenario, generate data instantly, audit it, and export as CSV, JSONL, GPT, or Ollama formats. Runs entirely in the browser using your own Gemini API key. No login. No servers. No data storage.
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Maker
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👋 Hey Product Hunt!
I built Synthetic Data Factory after repeatedly running into the same problem:
fine-tuning models is easy, creating good datasets is not.
For niche cases like OCR-heavy NER tasks, datasets often don’t exist, and hand-writing JSONL files is painful.
This tool generates structured, realistic synthetic datasets directly in the browser using your own Gemini API key, no login, no servers, no data storage.
I’d love feedback from folks working on ML, OCR, NER, or LLM fine-tuning.
What kinds of datasets do you struggle to create today?
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As a ML engineer, this product saves a lot of time instead of creating prompts from scratch to struggle with llms to create fake data, since the solution is tailored for it, it reduces half of the load while the dev can focus on customising data !!
As a ML engineer, this product saves a lot of time instead of creating prompts from scratch to struggle with llms to create fake data, since the solution is tailored for it, it reduces half of the load while the dev can focus on customising data !!