The quality of your logs is critical. Our algo/LLM has no idea about your code but the "Logs". We currently push toward standardizing Otel based logs. You can read about it here https://opentelemetry.io/docs/specs/otel/logs/

Please upvote if you lie our idea: https://www.producthunt.com/products/logclaw

And YES LogClaw.ai is able to injest terabytes of logs a day.

Also developer configure the alerting conditions. LogClaw it automatically finds your incidents with out manual setting up alerting conditions on your log dashboard [splunk/datadog logs]

Analyzing logs is not a LLM Foundation model issue.

LogClaw algorithm is the moat here that flags logs first. Those only flagged usually less than 10% of the logs are analyzed by LLM. LLM is great at finding root cause if the logs are clear and detailed. So the LLM heavily depends on the quality of your logs. So if your logs are rich with info, it will have a better insights at understanding it.

I'm waiting for Anthropic's Email. I guess it is not as important as OpenClaw.

Appreciate it. try logclaw, we need your software insights on it.

I meant since this is designed to be deployed in companies private VPC, their data stays with them. Zero vendor data risk. Corrected it. Thanks for pointing it out.

Thanks for pointing out. Try logclaw and we need your input instead,