The idea came from a pain I kept hitting as a founder — every time I had a new product idea, I'd spend hours manually Googling market signals, comparing competitors, and trying to gut-check whether it was worth pursuing. That process was slow, inconsistent, and didn't scale. So I built AIdeator: a local-first idea validation engine that turns raw product ideas into structured reports with demand, competition, and risk scores (0–100) — in minutes, not hours. The thing I'm most proud of is the privacy model: you can run it fully offline with Ollama and DuckDuckGo with zero data leaving your machine, or plug in cloud LLMs (OpenAI, Anthropic, Mistral) and AI search (Tavily, Exa) for deeper signals. You control exactly what leaves your system. It also benchmarks your idea's scores against 12 reference SaaS products, so you get a percentile rank, not just a raw number. It's fully open-source (MIT) and available on PyPI — pip install aideator and you're up in under 2 minutes. Would love to hear: what's your current process for validating product ideas before building? Drop it below — genuinely curious how others approach this! 🚀