How Ember works
Ember is AI-assisted incident intelligence for engineering teams. It turns weak signals from everyday work into shared context, serves explainable recommendations, and builds incident memory your org can reuse, with humans in the loop at every step.
Step 1
Ember pulls in what you already produce: conversations from chat platforms, code changes, and alerts and telemetry from observability. No rip-and-replace: the inputs are the same signals your team was going to generate anyway.
Step 2
Instead of chasing tabs, you get one coherent view of what is happening, what changed, and what likely matters now versus what can wait. The goal is legibility under pressure, so responders spend less time reconstructing the story and more time deciding what to do.
Step 3
Ember proposes concrete actions your team can confirm, edit, or ignore. Each suggestion ships with plain-language reasoning tied to the context above (not a black box). What you validate becomes part of incident memory for the next time a similar situation shows up.
What it looks like
A stylized example of how Ember presents a situation: symptoms, the change that lines up, why it matters, and a suggested move you can act on.
Illustrative example. Not live data.
Ember is software for people who carry the pager. It amplifies context and options. It doesn't replace ownership.
Integrations
The same chat, code, and observability surfaces where weak signals show up first.
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