Alternatives
Products that do what PySynthData does
Generate realistic synthetic data at scale
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Hey HN, we're Evis and Nick and we're excited to be launching Neosync (https://www.github.com/nucleuscloud/neosync). Neosync is an open source platform that helps developers anonymize production data, generate synthetic data and sync it across their environments for better testing, debugging and developer experience. Most developers and teams have some version of a database seed script that creates some mock data for their local and stage databases. The problem is that production data is messy and it’s very difficult to replicate that with mock data. This causes two big…
2024 · github.com
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2025 · github.com
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Source-backed technographics with an API and MCP server.
Feb 2026
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2018 · github.com
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Hey HN! A few months ago we shared our AI dataset generator as an open source repo, and the response was incredible (https://news.ycombinator.com/item?id=44388093). We got requests from folks who wanted to use it without the hosting overhead, so we created both options: a hosted version (https://www.metabase.com/ai-data-generator for instant use and the source code fully open (https://github.com/metabase/dataset-generator) for anyone who wants to self-host or contribute. Looking forward to seeing how you use it and what you build on top of…
Sep 2025 · metabase.com
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Hey HN, We just shipped a new AI-powered feature... BUT the "AI" piece is largely in the background. Instead of relying on a chatbot, we've integrated AI (with strict input & output guardrails) into a workflow to handle two specific tasks that would be difficult for traditional programming: 1. Identifying the most relevant base URL from HAR files, since it would be tedious to cover every edge case or scenario to omit analytics, tracking, and other network noise. 2. Generating synthetic data for API requests by passing the API context and faker-js functions to GPT-4. The steps are broken down…
2024 · docs.multiple.dev
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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