Ask HN: Do you struggle analyzing large log files with AI due to token limits?

I've been working on a tool that compresses log files for AI analysis. In my tests, I reduced a 600MB log file down to 10MB while preserving 97% of the semantic meaning — the AI could still understand the full context, errors, and patterns.

The approach uses symbolic encoding specifically designed for how LLMs process information, not just standard compression.

Curious if others face this problem regularly:

1. Do token limits stop you from feeding full logs to AI? 2. What's your current workaround? 3. Would a tool like this be useful in your workflow?

Not selling anything — just trying to understand if this is a real pain point before building further.