Multi-Layer, Continuous AI

Möbius is the multi-layer, continuous AI that drives Dstl8. Möbius consists of three key layers:

Edge Distillation Layer: Möbius begins at the edge, reducing raw telemetry into structured summaries of sentiment, severity, and signal flow.
Operational Inference Layer: Across clusters, Möbius aggregates and correlates patterns and trends, summarizing issues and detecting anomalies.
Continuous Agentic Layer: Möbius SRE-Ops agents analyze, explain, and learn from every signal, continuously investigating and surfacing issues and impact.

The result: always-on operational intelligence that turns observability into understanding.

Mobius Continuous AI

Continuous Agentic Layer

Möbius agents continuously monitor distilled telemetry from the edge distillation and operational inference layers to detect, investigate, summarize, and help resolve every incident at the enterprise level. Agents assign events to incidents, manage their lifecycle, and supply supporting detail for deeper exploration and validation. MCP server enables integration with any AI.

• Continuously watch distilled signals
• Detect, categorize, manage incidents
• Explain issues in plain language
• Facilitate deeper exploration, understanding

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Operational Inference Layer

Möbius SLMs connect signals across services, clusters, and workloads, revealing common patterns and shared root causes. This aggregates edge data into local and regional trends to better inform Möbius agents at the global level.

• Identify local and regional patterns
• Refine and crystallize trends
• Collect supporting log evidence detail

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Edge Distillation Layer

Traditional observability is top-heavy by design: collect everything, analyze later. Möbius inverts that triangle to analyze telemetry at the edge distilling signals into a compact, contextual format that AI can actually use. Optimizes telemetry to fit the context windows and real-time input needs of Möbius continuous AI.

• Continuously monitor, distill logs at the edge
• Reduce raw telemetry into structured summaries
• Identify sentiment, severity, counts
• Forward for downstream AI analysis

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