PLAYBOOK · TELECOMMUNICATIONS

A NOC copilot that already read every runbook.

Network Operations Centers handle alarm storms with runbooks that age out of memory. This playbook turns OSS/BSS endpoints into Custom HTTP tools, indexes runbooks into a vector store, and lets a triage network recommend the right remediation per alarm signature.

OSS/BSS APIsRunbook RAGNetwork OrchestrationSEEMR
Network Labs for NOC triage
The problem

Alarms flood faster than humans triage

OSS/BSS alarms arrive at thousands per minute. Engineers context-switch between alarm consoles, ticketing tools, and wikis of runbooks. The remediation knowledge exists — it's the discovery that breaks under load.

The VDF AI approach

Correlate, retrieve, recommend

The triage network maps each alarm to the most relevant runbook, calls OSS APIs to gather context, and proposes a remediation playbook with a confidence score. Engineers approve or override.

REFERENCE ARCHITECTURE

From alarm signature to remediation

OSS/BSS Alarms
SNMP · Kafka feed
Custom HTTP Tools
topology · ticket · CMDB
Runbook RAG
pgvector
Correlator Agent
Runbook Retriever
Remediation Planner
NOC Triage Network
Intent: triage-alarm
Recommended action + ticket draft
PLAYBOOK · STEP BY STEP

From alarm to guided remediation

1

Wrap OSS/BSS APIs as Custom HTTP tools

Topology lookup, CMDB query, ticket create — each becomes a typed tool VDF agents can call.

2

Vectorize runbooks and post-mortems

Markdown, Confluence, Word — VDF Data ingests them all. Per-region indexes scope retrieval.

3

Build the triage agents

The correlator groups alarms by signature, the retriever finds matching runbooks, the planner emits a remediation with risk and ETA.

4

Compose the Network

Intent template triage-alarm binds correlator → retriever → planner. SEEMR routes by alarm severity.

5

Operate at NOC scale

Live Execution Monitoring exposes per-alarm flows. Energy tracking shows the cost of each recommendation.

NOC triage network monitoring
OUTCOMES

Fewer escalations, faster MTTR

−40%

MTTR on known alarm signatures.

engineer throughput during alarm storms.

100%

recommendations carry runbook citations and topology evidence.

SEEMR REFERENCE

Routing for criticality

P1 alarms route to your most capable private model. P3 maintenance signals route to small models. SEEMR learns the boundary as your network evolves.

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You Have Questions

Tell us what you’re trying to achieve—governed AI Networks, enterprise RAG, deep integrations, or on‑premise deployment. We’ll help you map the right architecture, security posture, and rollout path. If you’re moving beyond AI pilots and need scalable, auditable execution, reach out—our team is ready to help.