Network OAM and Performance Operations Copilot

Knowledge-enhanced assistant for telecommunications configuration management that helps interpret complex operation, administration, maintenance, and performance information to support faster network operations workflows.

The Problem

“Network OAM and Performance Operations Copilot for Faster Telecom Operations Decisions”

Organizations face these key challenges:

1

Operational data is split across structured OSS systems and unstructured documents

2

Alarm floods and KPI degradations are difficult to interpret quickly

3

Vendor-specific terminology and procedures create cognitive overhead

4

Runbooks are outdated, inconsistent, or hard to find during incidents

Impact When Solved

Reduce time spent searching across OSS, manuals, and ticketsImprove first-response quality for alarms and KPI degradationsStandardize troubleshooting guidance across vendors and teamsShorten escalation cycles by packaging relevant evidence automatically

The Shift

Before AI~85% Manual

Human Does

  • •Search OSS views, manuals, runbooks, and past tickets for relevant network context
  • •Interpret alarms, counters, KPI degradations, and configuration states across affected nodes
  • •Correlate recent changes, maintenance activity, and topology relationships to form a diagnosis
  • •Decide troubleshooting steps, escalate to experts, and document incident findings manually

Automation

    With AI~75% Automated

    Human Does

    • •Confirm incident priority, operational impact, and the troubleshooting path to pursue
    • •Approve sensitive diagnostic steps, maintenance checklists, and any recommended corrective actions
    • •Handle ambiguous cases, policy exceptions, and cross-domain tradeoff decisions

    AI Handles

    • •Continuously gather and unify alarms, KPIs, configuration snapshots, topology context, documents, and ticket history
    • •Explain network conditions in plain language, summarize anomalies, and surface grounded troubleshooting guidance with citations
    • •Correlate degradations with recent changes and affected nodes, then assemble evidence and draft incident summaries
    • •Run approved read-only diagnostics, generate pre-check and post-check checklists, and package escalation-ready evidence

    Operating Intelligence

    How it works

    AI surfaces what is hidden in the data.

    Humans do the substantive investigation.

    Closed cases sharpen future detection.

    Confidence91%
    ArchetypeDetect & Investigate
    Shape6-step funnel
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapefunnel

    Step 1

    Scan

    Step 2

    Detect

    Step 3

    Assemble Evidence

    Step 4

    Investigate

    Step 5

    Act

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6↺ Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI scans and assembles evidence autonomously. Humans do the substantive investigation. Closed cases improve future scanning.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

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