Network event analytics
Analyzing network events as they arrive, on an event-driven data platform.
Industry
Technology for telecommunications and technology businesses
Telecom and technology businesses run services that depend on events, platforms and support teams. We help monitor them, analyze them and build the cloud-native platforms behind them.
In short
Nexstella helps telecommunications and technology businesses with network event analytics, service quality monitoring, customer experience analytics, intelligent technical support, cloud-native service platforms and usage forecasting and anomaly detection. Reliability targets and cost controls can be agreed as part of the design.
Last updated
01 Use cases
Where does technology usually help?
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Service quality monitoring
Monitoring and alerting that show how services perform against agreed targets.
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Customer experience analytics
Analytics that show how customers experience a service, on governed and agreed metrics.
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Intelligent technical support
Assistants that help support teams find answers, within defined access and action boundaries.
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Cloud-native service platforms
Designing and operating cloud-native platforms, with infrastructure and releases under code.
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Usage forecasting and anomaly detection
Forecasting usage and flagging anomalies, tested against representative cases before anyone relies on them.
A technology business runs service platforms whose infrastructure grew organically. They need stronger monitoring, alerting and cost controls.
We would assess the cloud architecture, then add monitoring and alerting against reliability targets agreed with you. Workload-level cost allocation would show where spending goes.
02 Considerations
What needs extra care in telecom and technology?
Production systems should have agreed definitions for reliability, and cost should be visible. These are the controls that can be set before the build begins.
- Service-level indicators and objectives, with availability and latency targets that reflect the criticality of the workload
- Alert thresholds and escalation paths, with incident management and post-incident reviews
- Capacity and scaling policies for the platform
- Cost visibility, including resource tagging, workload-level cost allocation and cost per transaction
- Cost optimization that preserves required performance, security and reliability
03 Capabilities
Which capabilities usually apply?
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Cloud, DevOps and platform engineering
Secure cloud foundations, infrastructure as code, containers and deployment you can repeat with confidence.
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Data engineering and modern data platforms
Pipelines, warehouses and lakehouses that make business information reliable, governed and ready for analytics and AI.
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Generative AI, agentic AI and intelligent automation
Knowledge assistants, document processing and bounded agent workflows, with evaluation and human approval where it matters.
Common starting points
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Growing technology
For growing businesses whose infrastructure, data and releases need to keep pace with more users and complexity.
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Specialist engineering
For companies with their own engineers who need specialist skills, architecture advice or extra capacity.
04 Questions
What do people usually ask?
Network event analytics and service quality monitoring are both within what we support. Event-driven architecture suits real-time events, operational monitoring and streaming applications, and alert thresholds and escalation paths can be agreed as part of the design.
An operational assistant can help engineers investigate incidents, retrieve runbooks and summarize logs. A support assistant can prepare responses within defined access and action boundaries. Both are evaluated before launch, and consequential actions keep a human approval step.
Solutions
Which solutions do we build for this?
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Agentic workflow automation
We build workflows where AI coordinates steps, uses only approved tools, checks intermediate results and escalates the decisions that need human judgment.
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Real-time data
We build streaming pipelines that ingest and process high-volume events, so people and systems can act on current information.
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DevOps automation
We automate how code and infrastructure are built, tested, scanned and deployed, with approvals and rollback, so releases rely less on manual steps.
If this sounds like you: Connect network, service and customer data before adding AI