Autonomy you can revoke.
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.
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.
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.
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 layer
over the estate you already run.
Intent goes in at the top. The platform decomposes it, assigns it to domain specialists, grounds every decision in your live data, and executes across every telco layer through standard interfaces. Observability feeds it continuously. Your existing systems stay where they are.
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.
Observe
Continuously500+ sources across RAN, core and transport, normalised into one model. Alarms, KPIs, tickets, inventory and topology in the same picture.
Investigate
Root causeFault chains traced across topology, telemetry and change history until the cause is separated from its symptoms, with the evidence attached.
Act under governance
Approval gateApproved procedures execute inside a defined blast radius. No defined reversal means no autonomy. The procedure stays advisory until it has one.
Verify and learn
Proof, not hopeService state is confirmed restored before the loop closes, and the outcome feeds the next occurrence. A fix that did not hold is not a closed ticket.
Specialists, not a general-purpose chatbot.
Each agent owns a slice of your operation, observes it continuously, and feeds every decision back into the shared intelligence layer, so what one agent learns, the next one inherits.
Network Agent
Network operationsPredicts degradations before they become incidents. Maintenance shifts from reactive to proactive.
- RAN, fiber and transport health monitoring
- Anomaly detection with early-warning signals
- Proactive maintenance dispatch and risk surfacing
Service Assurance Agent
Service qualityProtects service commitments instead of explaining failures after they happen.
- End-to-end service quality tracking across domains
- Fault correlation across network, service and customer layers
- Remediation triggered before SLAs breach
Business Ops Agent
Revenue operationsKeeps revenue flowing. Surfaces leakage before it becomes margin loss.
- Order fulfilment tracking across B2B and B2C
- Billing anomaly detection in real time
- Automated exception handling to accelerate fulfilment
Data Analytics Agent
Operational intelligenceTurns live operational data into decisions, not reports teams read a week later.
- Continuous mining for capacity metrics and forecasts
- Demand shift detection from live evidence
- Decision-ready insight surfaced to planning teams
The three that close it.
Sherlock
Reasoning agentDiagnoses root cause across topology, telemetry and change history in under two seconds.
- Multi-hop fault chain tracing across domains
- Source-linked reasoning. Every conclusion auditable
- Turns correlation into executable RCA automatically
ProcBot
Action agentExecutes remediation at machine speed, with rollback safety on every action.
- Approved runbooks with parametrised safety gates
- SoP / MoP actions scoped to authorised domains only
- Operators stay in control while routine fixes run autonomously
NOC Copilot
Engineer’s agentGives L1 and L2 teams a natural-language console for live network state. No dashboard trail needed.
- Ask about network state, get sourced actionable answers
- Guides decisions with context, not just data
- Escalation rules keep high-risk actions in operator hands
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.
The controls that make autonomy acceptable.
Every operator we talk to asks the same question before they ask about accuracy: what happens when it is wrong. These four controls are the answer, and they are the reason the platform is allowed near a production network at all.
Full provenance
Every agent action records the request, the response, the decision path and the source data lineage. Operators can replay what happened and prove why it happened, to an auditor or to a regulator.
Scoped access
RBAC and ABAC define what each agent can see and do, by domain and by data class. An agent never reaches beyond the authority assigned to its loop.
Kill switches
Disable action at agent, workflow or platform level. The controls sit with operations, so containment never waits on a code release or a vendor ticket.
Human in the loop
Risk thresholds route selected decisions to operator review before execution. Each loop type sets its own escalation rules, from advisory through to autonomous.
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.
Advisory
Analyses, scores and recommends. Takes no action. This is where accuracy is proven against your estate rather than promised in a deck.
- Root cause analysis
- Risk scoring
- Churn and capacity forecasting
Human-approved
Proposes a specific action with its evidence, and waits. A named engineer or a change board approves before anything executes.
- MOP execution
- Retention offers
- SLA credit computation
Closed-loop
Acts within policy bounds, with automatic rollback. Reserved for procedures that are high-volume, well understood and fully reversible.
- Alarm grouping and correlation
- Logical self-heal
- Standard provisioning
A procedure with no defined reversal is not eligible for stage three. That is a rule in the platform, not a guideline in the documentation.
What operators actually got.
Figures below come from a Tier-1 mobile operator running RAN fault management fully on-premises, across roughly 12.5 million alarms a day, over a twelve to eighteen month deployment. Results measured on one operator's estate are not a forecast for yours, which is why every engagement starts by baselining your own.
Under 2 seconds
Root cause delivered across topology, telemetry and change history.
500+ sources
Ingested in real time across RAN, core, transport and business systems.
Zero egress
Air-gapped deployment available. Model weights and inference stay inside your perimeter.
One fault class. Not a transformation programme.
The fastest path to value is not deploying every agent at once. Pick a single fault class that is high-volume, well understood and fully reversible. Something your team clears predictably forty or more times a month. Run it in advisory mode until the reasoning earns your trust. Then grant execution authority on that one procedure, and expand from there.
Targeted deployments go live in weeks, not quarters, and nothing gets ripped out to make room.
Bring us your noisiest fault class.
We will map it against the governed loop, show you where the approval gate would sit, and tell you honestly whether it is a fit. If your topology and inventory data are not yet reliable enough for autonomy, we would rather say so before you buy anything.
Worth a conversation
with your team?
Contact NetSingularityTell us where you're losing the most ground. We'll show you exactly where Netsingularity fits. And where it doesn't. A structured technical walkthrough on your use case, your data patterns.
Share the use case, team context, and email. We'll follow up with a focused walkthrough for your network lifecycle priorities.