Service Providers
Modern observability, automated operations, and an architecture built for what's next.
Modernize the observability, operations, and architecture behind your network, so you can see what's happening and grow without adding headcount for every new service.
Sound familiar?
Monitoring is a patchwork of tools that each see part of the network
The NOC reacts to outages instead of getting ahead of them
Operations don't scale: every new service means more manual toil
The OSS/BSS architecture is aging and expensive to change
Inventory drifts from reality, so automation can't be trusted
Mean time to resolution is too high, and getting worse as complexity grows
Communications and network service providers run some of the most complex operational environments anywhere, and the pressure never lets up. Traffic and service counts keep climbing while margins thin, and operations built for a simpler network strain to keep up. Adding another monitoring dashboard or another manual runbook doesn’t fix that. Modernizing how you observe, operate, and architect the network does.
This is the work we know best. We modernize the three things that determine whether a provider scales profitably: observability (can you actually see what the network and services are doing?), operations (does the NOC scale with the network, or with headcount?), and architecture (is the OSS/BSS estate an asset or an anchor?). Increasingly that includes bringing AI into operations where it actually pays off. We’ve built AI-assisted NOC workflows on real provider systems.
Where we help
Modern observability. Replace tool sprawl with unified, standards-based observability (OpenTelemetry, metrics, logs, and traces) so the network and the services on it are actually visible, end to end.
Operations modernization. Get the NOC ahead of outages instead of chasing them: automation that scales operations, closed-loop workflows, and AI-assisted triage and remediation where it proves out in practice. (See our NOC in a Box writing.)
Architecture modernization. Evolve aging OSS/BSS and service architectures toward something cheaper to change and ready for the next generation of services.
Trustworthy inventory. Reconcile network inventory and source-of-truth data so the automation you build on top can actually be trusted.
Lower MTTR. Bring monitoring, inventory, and ticketing into one operational picture so incidents get resolved faster, with less firefighting.
How we work
Our starting point is how your operation actually runs today. From there we design the modern target (observability, operating model, and architecture) and lead the delivery. The goal is an operation that scales with your ambitions instead of your headcount.
How we work
Assess operations & architecture
We evaluate how your NOC actually runs, where observability is blind, and where the OSS/BSS architecture is holding you back.
Design the modern target
We design modern observability, an automatable operating model, and the architectural changes to get there, including where AI-assisted operations genuinely help.
Deliver and enable
We build it hands-on (telemetry, automation, AIOps, and inventory you can trust) and leave your team running a modern operation, not a pile of tools.
What we help you build toward
We're not handing over a boxed product. We bring the expertise, and your team ends up owning a result like this:
Unified, modern observability across the network and services
A NOC that detects and resolves faster, with AI applied where it makes a difference
Operations that scale with the network, not with headcount
A modern service and network architecture that's cheaper to evolve
Trustworthy inventory as the foundation for real automation
Materially lower mean time to resolution
Case studies
Work we've done in this space
A unified data foundation for a global, multi-metro network
Inside a multi-year program, we led the systems-integration workstream. That meant NetBox as a single source of truth, a NetBox-driven DNS pipeline, unified AAA on ClearPass, and a global time network.
Event-driven network automation with AI-assisted troubleshooting
We built an event-driven, Kubernetes-native automation platform for a network operator: KEDA-scaled workers driven by Splunk and Salesforce events, plus LLM-assisted troubleshooting (LangChain Deep Agents, human-in-the-loop, blackboard pattern) that triggers automated on-site testing the moment an issue appears.
Platforms & technologies we work with
…and whatever else your environment runs on.