Network Performance Agent
Detects KPI degradation per cell and region
Tool: Anomaly detection · Source: Network performance counters
Industry
Telecommunications AI agent operations
Radio and core network performance, coverage maps and customer experience data
Operational layers in view
Network KPIsCoverage mapAlarm streamCustomer experienceCapacity plan
Network Performance Agent
Fault Correlation Agent
Coverage Agent
Capacity Planning Agent
Customer Impact Agent
Field Dispatch Agent
Node activity below is a demonstration using sample telecommunications data.
Ask the live agents
Describe the problem in your own words. We classify the industry, assign specialist agents, and you watch the workflow run and produce the visual deliverables — maps, dashboards, charts, tables and reports — instead of one block of text.
Demo mode uses clearly labelled sample data — never presented as verified.
Assigned specialists
Telecommunications
- Network Performance Agent
- Fault Correlation Agent
- Coverage Agent
- Capacity Planning Agent
- Customer Impact Agent
- Field Dispatch Agent
Deliverables planned
Interactive map
Charts
Dashboard
Data tables
Pauses for human approval
NOC approval
Workflow the run follows
- 1. User request
- 2. Requirement validation
- 3. Industry classification
- 4. Specialist agent selection
- 5. Data and file collection
- 6. Tool authorisation
- 7. Execution plan
- 8. Multi-agent collaboration
- 9. Analysis or generation
- 10. Quality validation
- 11. Human approval
- 12. Visual deliverables
- 13. Monitoring and audit
Demo
Telecommunications AI agent operations centre
Workflow: Counters and alarms received → Monitor recovery · Run pending · started — · elapsed 0s
Active agents
0
Tasks running
0
Completed steps
0/9
Tool calls
0
Human approvals
1
Warnings
0
Success rate
0%
Est. completion
36s
Active agents
Pending
Fault Correlation Agent
Groups alarms into probable root causes
Tool: Anomaly detection · Source: Network performance counters
Coverage Agent
Maps coverage gaps and interference
Tool: Anomaly detection · Source: Network performance counters
Capacity Planning Agent
Projects congestion and upgrade needs
Tool: Anomaly detection · Source: Network performance counters
Workflow canvas
Live activity stream
No activity yet. Start the demo run to watch telecommunications agents work through the workflow with sample data.
Demonstration using sample data — no real client operation is shown. Sign in and connect an approved AI provider and authorised industry data source to activate live execution.
Telecommunications specialist agents
Each agent owns one step of the workflow, with its own tools, inputs and approval level.
Autonomous
Network Performance Agent
Detects KPI degradation per cell and region
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Autonomous
Fault Correlation Agent
Groups alarms into probable root causes
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Autonomous
Coverage Agent
Maps coverage gaps and interference
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Review advised
Capacity Planning Agent
Projects congestion and upgrade needs
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Autonomous
Customer Impact Agent
Links network events to affected customers
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Review advised
Field Dispatch Agent
Proposes site visits and priorities
- Inputs:
- Network performance counters, Alarm feeds, Drive-test and coverage data
- Tools:
- Anomaly detection, Coverage modelling, Capacity planner
Solution blueprint
Operational context
Industry challenges
- Operational data for telecommunications is spread across disconnected systems
- Analysis-heavy work is repeated manually every cycle
- Risks and exceptions are found late
- Reporting and audit overhead grows with volume
Solution patterns
Recommended AI solutions
- Specialist agents that own one step of the workflow each
- Grounded retrieval over your permitted systems only
- Predictive scoring with explainable reasons
- Approval-gated execution into your systems of record
Data readiness
Required data
- Network performance counters
- Alarm feeds
- Drive-test and coverage data
- Customer tickets
Controlled process
Example workflow
- Counters and alarms received
- Validate feeds
- Detect degradation
- Correlate faults
- Map coverage impact
Connection points
Integration opportunities
- OSS / BSS
- Network management
- GIS coverage services
- Support desk
Measure after baseline
Expected outcomes
- Analysis cycle time
- Manual review effort
- Decision auditability
- Earlier risk detection
Governance controls
Security and compliance
- Row-level security scopes every read to the requesting organisation
- Retrieval is limited to documents the user may already open
- Every agent action, tool call and approval is written to the audit log
- Sensitive steps pause until a named human approves them
Inputs, integrations and outputs
Inputs
- • Network performance counters
- • Alarm feeds
- • Drive-test and coverage data
- • Customer tickets
Integrations
- • OSS / BSS
- • Network management
- • GIS coverage services
- • Support desk
Outputs
- • Degradation report (PDF, CSV)
- • Coverage impact map (GeoJSON)
- • Network dashboard (Dashboard)
Business outcomes to baseline and measure
Analysis cycle time
Target and measurement method agreed during discovery.
Manual review effort
Target and measurement method agreed during discovery.
Decision auditability
Target and measurement method agreed during discovery.
Earlier risk detection
Target and measurement method agreed during discovery.
No performance result is promised before a baseline is measured. Targets are agreed for each engagement and reported against real delivery data.
How This AI Agent Works
The process the telecommunications agent team follows, from trigger to approved deliverable.
Spatial analysis workflow
From uploaded spatial data to a validated result layer, statistics and exports.
Workflow preview
Saved with the run so the recorded execution trail shows what was asked. Demonstration runs use sample data. They do not touch your systems.
Public visitors can preview the structure and inspect every node. Labelled demonstrations and live runs require a signed-in account with configured providers.
72%
Workflow summary as a text list
- 1. Upload spatial data: Input. GeoJSON, shapefile export or feature service reference.
- 2. Validate GeoJSON and CRS: Validation. Check geometry validity, projection and feature count.
- 3. Add to map: Action. Render the source layer on the workspace map.
- 4. Select spatial tool: Decision. Choose buffer, overlay, proximity or zonal statistics.
- 5. Run geoprocessing: Approved tool. Execute the selected operation on the spatial service.
- 6. Validate geometry: Validation. Check topology, area totals and null geometries.
- 7. Generate result layer: AI agent. Assemble the analysis layer and its statistics.
- 8. Specialist review: Human approval. A GIS specialist approves before results are released. Human approval required.
- 9. Map, statistics and export: Output. Interactive map, statistics table and GeoJSON download.
Approval gate: Specialist review. Deliverable: Map.
Workflow audit for this page
Structure only. Run a demonstration to include events.
| Template ID | Nodes | Approval node | Output type | Preview | Demo | Live | Mobile test |
|---|---|---|---|---|---|---|---|
| gis-analysis-agent | 9 | Yes. Policy: always | Map | Available | Available (signed in) | Available via Studio · requires ai_provider, python_service | Verified at 390px |
Demonstration runs are stored and replayed from recorded events. Live runs execute server-side in the Studio and only start when the listed integrations report healthy.
Relevant case study
Illustrative case study
Wastewater network GIS for a national water utility
A wastewater network needed utility-GIS structuring, mapping and quality-controlled network intelligence for daily operations.
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