Ember connects chat signals, code changes, and observability into one timeline, surfaces explainable next steps, and builds incident memory your team can trust, with humans in the loop at every step.
We'll only email when there's something worth saying.
Stylized preview of Ember's incident summary format. Not live data.
Product
Low-noise, human-in-the-loop workflows that stay aligned with how your team already responds, without black-box promises.
Context
Correlate deploys, alerts, diffs, and conversations from chat so everyone sees the same story, including the quiet signals that usually get lost.
Recommendations
Suggestions cite the signals behind them. Your team confirms, adjusts, or rejects. Recommendations stay grounded and improve over time.
Memory
Past incidents and decisions become reusable context: playbooks and risk hints surface when similar changes or patterns show up again.
Integrations
Ingest conversations, code changes, and telemetry together so weak signals add up before an alert fires.
From the blog
Deep dives on early signals, incident memory, and calmer on-call culture: the same ideas behind the product.
Postmortems are useful, but incident learning only matters if it can resurface when teams need it during future changes, signals, and incidents.
Read articleAI can help teams respond to incidents, but only if engineers can see the evidence, confidence, and reasoning behind its recommendations.
Read articleAI-assisted engineering makes it easier to ship change, but faster delivery increases the need for clear platform ownership, operational context, and evidence-backed incident response.
Read articleEarly access
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