Thanks for the follow-up. Let me try to clarify!
When we say we "organize all logs, metrics, and traces", we mean more than just linking them together (which otel already supports). What we’re doing is:
- context engineering optimization: We leverage the structure among logs, spans, and metadata to filter and group relevant context before passing it to the LLM. In real production issues, it's common to see 10k+ logs, traces, etc. related to a single incident — but most of it is noise. Throwing all that at agents usually leads to poor performance due to context bloat see https://arxiv.org/pdf/2307.03172. We're working on addressing that by doing structured filtering and summarization. For more details see https://bit.ly/45Bai1q.
- Human-in-the-Loop UI: For cases where developers want to manually inspect or guide the agent, we provide a UI that makes it easy to zoom in on relevant subtrees, trace paths, or log clusters and directly select spans to be included in the reasoning of agents.
The goal isn't just unification, it's scalable reasoning over noisy telemetry data, both automated and interactive.
Hope that clears things up a bit! Happy to dive deeper if useful.