AI-Powered RAN Fault Management
~60%Alarm noise reduced through AI correlation & deduplication
~50%Faster mean time to resolve (MTTR) across incident families
~40%Improvement in NOC L1/L2 headcount efficiency
AI Governed Operations
Autonomy you canrevoke.
Most AI in telecom writes you a better ticket. NetSingularity closes the loop. It detects the fault, works out why, executes the fix, and proves the service is back. Zero-touch where you allow it. Human-approved where you require it. Every action recorded, scoped, and reversible.
The shift
Your NOC doesn't need more alerts.It needs fewer decisions.
Adding headcount to a noisy network absorbs more noise. It does not improve the picture any one engineer sees. Governed operations attacks the other side of the equation: the platform takes the repetitive, well-understood, reversible work off the queue entirely, and hands your engineers only the decisions that genuinely need a human.
What most platforms deliver
A better notification system
Alarms are grouped, scored, and rendered on a dashboard. A human still reads it, still decides, still executes, still verifies. The work never left your team. It just arrived better formatted.
What governed operations delivers
Completed work
The loop ends with the fault cleared and the service verified, with a record of what was decided, on what evidence, under whose authority, and how to undo it. The measure is work absorbed, not insight offered.
One governed intelligence layerover the estate you already run.
Intent is decomposed, grounded in live operational context and routed through specialist agents. Governance spans the path from request to verified action.
The governed loop
Four stages. One approval gate.Nothing that cannot be undone.
Autonomy is not a switch you flip. It is a set of permissions your engineers grant, one procedure at a time, and withdraw the moment they want it back.
Operator authority sets the boundary
Operator authorityPolicy / approval gateAct
- 01
Observe
Signals, events and operational context arrive.
- 02
Investigate
Evidence is correlated and the next action is determined.
- 03
Act
Approved work executes inside the allowed scope.
- 04
Verify
Live state proves whether the intended result occurred.
Action stays scoped, approved where required, reversible and auditable; verification confirms the outcome.
Service as Software
Explore Service as Software Governed autonomy is what letssoftware finish the work.
Agents can investigate, execute and verify approved work because authority, policy and rollback are part of the execution path.
Domain and execution agents
Specialists, nota general-purpose chatbot.
The planner delegates work to agents that understand specific operational domains. When execution is required, specialist agents carry the investigation through to verified close.
Planner
One intent
Domain specialists
- Network operations
Network Agent
Predicts degradations before they become incidents. Maintenance shifts from reactive to proactive.
- Service quality
Service Assurance Agent
Protects service commitments instead of explaining failures after they happen.
- Revenue operations
Business Ops Agent
Keeps revenue flowing. Surfaces leakage before it becomes margin loss.
- Operational intelligence
Data Analytics Agent
Turns live operational data into decisions, not reports teams read a week later.
Execution specialists
Sherlock · Reasoning agent
Diagnoses root cause across topology, telemetry and change history in under two seconds.
ProcBot · Action agent
Executes remediation at machine speed, with rollback safety on every action.
NOC Copilot · Engineer’s agent
Gives L1 and L2 teams a natural-language console for live network state. No dashboard trail needed.
What it looks like in practice
One intent. Seven steps.No ticket queue in between.
A planner types a goal in plain language. What follows is not a workflow someone has to drive. It is the platform decomposing the goal, pulling in the specialists each sub-goal needs, acting inside its permissions, and proving the result.
Built for live networks, not lab conditions
The controls that make autonomyacceptable.
Scope, approval, rollback and audit define what can act, when it can act, and how operators retain control.
Scope
Role- and policy-based access limits what each agent can see and touch, by domain and data class.
Approval
Risk and confidence thresholds route actions to the right operator before execution.
Rollback
Actions require a defined reversal path; operations can stop an agent, workflow or platform.
Audit
Decision, evidence, approval and action are traceable as one operational record.
Graduated autonomy
Agents earn authority.They are not granted it on day one.
Every loop starts in advisory mode on your live data. It moves up only when your engineers have seen enough of its reasoning to sign off on that one procedure, and it moves back down the moment they say so.
Stage 01
Advisory
Analyses evidence and recommends. No action is taken.
- Root cause analysis
- Risk scoring
Stage 02
Human-approved
Proposes a specific action; a named operator approves before execution.
- MOP execution
- Service remediation
Stage 03
Guardrailed
Executes only within defined policy, scope and confidence limits.
- Bounded action scope
- Escalation on exceptions
Stage 04
Closed-loop
Runs proven, reversible procedures and verifies the service outcome.
- Approved self-heal
- Automatic rollback
Authority advances by procedure, not by platform-wide switch; it can be reduced or revoked at any time.
Outcomes from shared case studies
What operatorsactually got.
Results from fault-management and change-management engagements show where governed automation can help. They are indicative outcomes, not a forecast for your estate.
Read the case study
AI-Powered Network Change Management
~30%Faster MOP preparation, validation and delivery cycle
80%Zero-touch execution on approved change categories (target)
100%Audit-ready traceability of every change decision and action
Improvement figures are indicative targets or expected outcomes; exact results vary by network scope, data availability and deployment phase. Zero-touch change execution is a target for approved categories.
Where to start
Start with one fault class.Expand when the evidence says to.
Contact NetSingularityPick a recurring fault with a measurable baseline. Begin in advisory mode, move through human-approved execution, and expand authority only when the evidence supports it.