Most LLM-based data tools simply throw entire datasets at models, resulting in astronomical token usage. Through a combination of zero data exposure and local query validation, I've reduced token consumption by 80% compared to standard approaches.

I'd love feedback from you, especially from those who've worked with the cost and complexity of data analysis. Would also appreciate thoughts on our approach to token optimization!

Try it out: https://www.thedataworkspace.com/

Comments URL: https://news.ycombinator.com/item?id=43444170

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Try it here: https://app.processly.ai Demo/How-to-use: https://youtu.be/Gpt2KBpMKas?si=7Nw_walC1KuFkhyz

What it does: 1. generate SQL and return its results while keeping the raw data private 2. ui to create and share dashbaords 3. affordable - it's like Tableau but for small busiesses

It is focused on simplicity, especially for non-technical teams. We'd love your thoughs.

Comments URL: https://news.ycombinator.com/item?id=42218070

Points: 1

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