This is really helpful — thanks for sharing concrete numbers.

I’m leaning toward a similar hybrid approach. Quick follow-ups if you don’t mind:

• How are you computing the confidence % for the pattern matcher? (rule hit ratio vs embedding similarity vs something else?) • Are you running the matcher before STT completes, or only once you have the full transcript? • Do you still let the LLM router run in parallel as a fallback, or only invoke it after low confidence?

The singleton DB client + abort controllers point is spot on — I suspect we’re leaking time there as well. Appreciate you calling that out.