Alarm and event correlation
Normalize and correlate events across systems, devices, network layers, services, and time.
Telecom & Mobile Operators
AI-Powered Telecom, Mobile & Network Operations
Connect alarms, topology, configurations, packet evidence, performance data, operational documentation, incidents, and network workflows through a private AI-assisted operating environment for telecom, mobile, ISP, and network teams.
Operator environments generate enormous amounts of state but still require experienced engineers to correlate alarms, understand topology, inspect packet behavior, retrieve procedures, compare changes, and determine the next safe action. OPTIME can engineer the intelligence, evidence, automation, and private infrastructure around those workflows.
WHY THIS MATTERS
Network state becomes useful when telemetry, topology, changes, and operating knowledge connect.
A network incident may involve alarms, configuration, routing, topology, packet captures, logs, KPIs, capacity, recent changes, vendor systems, runbooks, and engineer knowledge.
These sources often use different identities, clocks, formats, and ownership models.
A generic assistant cannot safely operate the network without an authoritative model of state, topology, permissions, supported actions, and failure behavior.
Turn network telemetry, alarms, topology, configurations, packet evidence, operational knowledge, and engineering workflows into a private AI-assisted network-operations environment.
SYSTEM PRESSURES
Why simple implementations break down.
Alarm volume obscures causality
Several symptoms may originate from one dependency, change, path, or capacity issue.
Operational knowledge is fragmented
Runbooks, tickets, documentation, vendor notes, and engineer experience are difficult to retrieve during incidents.
Configuration and telemetry are disconnected
Teams cannot easily connect a change with later network behavior.
Packet evidence arrives late
Packet-level investigation may be separate from NOC and service-assurance workflows.
Capacity decisions lack full context
Traffic, sessions, topology, hardware, software, and service priorities may be analyzed independently.
Automation lacks bounded authority
Scripts or AI-driven actions may not understand topology, convergence, partial failure, or rollback.
COMPLETE SOLUTION
Engineer the workflow as one controlled production system.
The complete system can connect alarms, events, topology, configuration, routing state, mobile-core state, packet captures, performance metrics, logs, tickets, changes, runbooks, network documentation, private LLMs, retrieval, anomaly signals, incident correlation, capacity analysis, workflow automation, human approval.
CAPABILITY GROUPS
What the complete Solution can contain.
Incident investigation
Build one evidence timeline connecting alarms, topology, configuration, recent changes, packets, logs, and service symptoms.
Operational knowledge
Provide permission-aware retrieval across runbooks, tickets, architecture, procedures, vendor material, and internal knowledge.
Configuration and change intelligence
Compare intended and observed state, identify relevant changes, and connect changes with later behavior.
Packet and protocol evidence
Integrate packet captures, protocol analysis, flow telemetry, and session state into incident and capacity workflows.
Capacity and performance analysis
Combine traffic, sessions, routes, hardware, resource use, service priority, and growth assumptions.
Anomaly and fraud indicators
Surface configured unusual patterns for investigation without declaring fraud or root cause as fact.
Controlled automation
Allow approved diagnostics, queries, or corrective actions through bounded tools, permissions, validation, and rollback.
NOC and engineering interfaces
Provide role-specific views for operators, core engineers, IP teams, capacity teams, and incident leaders.
ARCHITECTURE FLOW
Connect the complete path from source and session to operation.
The flow begins with network devices, mobile core, radio, transport, services, and applications and preserves control through every processing and operating layer.
Network devices
Network devices, mobile core, radio, transport, services, and applications
Alarms
Alarms, events, topology, configurations, logs, tickets, and change records
Packet captures
Packet captures, flow telemetry, protocol state, and performance metrics
Source normalization
Source normalization, time correlation, identity mapping, and evidence graph
Private LLM
Private LLM, retrieval, anomaly analysis, and specialist network models
Incident
Incident, capacity, configuration, and operational reasoning
Recommended diagnostics
Recommended diagnostics, explanations, exceptions, and approved actions
NOC
NOC, engineering, capacity, and incident-team review
Bounded automation
Bounded automation, ticketing, change, and reporting integration
Evaluation
Evaluation, access controls, model lifecycle, and operational ownership
ARCHITECTURE DECISIONS
Make important trade-offs explicit before they become operating constraints.
Centralized AI or domain-specific assistants
Approach A
Centralized AI
Approach B
domain-specific assistants
Selection considerations
Use specialized retrieval and tools for IP, mobile core, radio, service assurance, and capacity where their data and actions differ.
Passive analysis or active automation
Approach A
Passive analysis
Approach B
active automation
Selection considerations
Begin with evidence and recommendations before permitting controlled network actions.
Central data copy or federated source access
Approach A
Central data copy
Approach B
federated source access
Selection considerations
Preserve source authority and reduce unnecessary replication where practical.
General models or specialist network models
Approach A
General models
Approach B
specialist network models
Selection considerations
Use deterministic parsers, graph analysis, time-series methods, protocol tools, and domain models where appropriate.
Real-time or post-incident analysis
Approach A
Real-time
Approach B
post-incident analysis
Selection considerations
Apply real-time correlation when operational value justifies the required scale and reliability.
REPRESENTATIVE SCENARIOS
How the Solution applies in representative situations.
Representative examples: Each operational scenario correlates network evidence and controlled tooling without giving a model unrestricted authority over the network.
Alarm storm investigation
- Scenario
- The system groups related alarms, correlates topology and changes, and prepares a source-backed incident hypothesis.
Mobile-session troubleshooting
- Scenario
- Registration, signaling, user-plane, packet, and subscriber evidence are connected for engineering review.
Capacity review
- Scenario
- Traffic, service demand, sessions, hardware, routes, and historical growth contribute to a capacity recommendation.
Change-impact analysis
- Scenario
- A configuration change is linked to affected devices, paths, KPIs, incidents, and rollback evidence.
NOC knowledge assistant
- Scenario
- Operators retrieve the correct runbook, previous incident, architecture, and approved diagnostic procedure.
Bounded diagnostic automation
- Scenario
- The assistant runs approved read-only queries and assembles the result without broad network authority.
ENGAGEMENT APPROACH
Move from operating context to a validated production system.
Phase 1
Operations and data-source assessment
Map telemetry, alarms, topology, configurations, tools, incidents, network domains, permissions, and operational workflows.
Phase 2
Representative incident or capacity pilot
Prove one cross-layer investigation using real historical or controlled data.
Phase 3
Operations-intelligence implementation
Build connectors, evidence graphs, private AI, interfaces, tools, and workflow integration.
Phase 4
Controlled rollout and evaluation
Validate incident quality, false correlations, permissions, automation boundaries, scale, and ownership.
POSSIBLE DELIVERABLES
Evidence and implementation that can transfer into operation.
Network-operations AI architecture
Alarm and event-correlation pipeline
Incident evidence graph
Private NOC assistant
Operational knowledge system
Packet and protocol integration
Configuration and change analysis
Capacity-analysis workflow
Bounded diagnostic tools
Ticketing and reporting integration
Private model infrastructure
Evaluation and operational controls
Final deliverables depend on the selected architecture, validation evidence, and engagement scope.
Start with the workflow, evidence, integration, deployment, performance, and operating constraints that determine whether this system can work in production.
START A TECHNICAL CONVERSATION
Discuss the system, constraints, and engineering outcome.
Share the product, workload, architecture, infrastructure, performance, security, or delivery constraint that must be resolved.
Austin, Texas
Distributed engineering teams across North America, Europe, the Caucasus, and Latin America.
[email protected]