Independent Analysis: AI, SaaS, and Revenue Growth Strategy

Every time you make a video call, stream a film, or transfer a file across continents, that data moves through infrastructure that someone has to manage in real time. The companies doing that managing — carriers, telecom operators, large enterprise network teams — have spent decades accumulating tools, systems, and processes that were never designed to work together. The problem those organizations face today is not a technology shortage. It is a complexity debt that compounds every year, and the cost of servicing it is becoming a strategic liability.

This piece explains the space those organizations are trying to modernize, the technology concepts that matter, and the vendors competing to own that modernization. Blue Planet, a division of Ciena, is the anchor for this analysis, but understanding Blue Planet requires understanding the problem it exists to solve.

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The Legacy Complexity Problem

Large network operators grew through acquisition and technology generations. Each decade brought new protocols, new vendors, and new management tools layered on top of the last. The result, for many carriers, is a network management estate that looks less like a system and more like an archaeological site: 40 years of equipment generations, dozens of vendor-specific element management systems, and no single source of truth for what is actually connected to what.

Lumen Technologies, one of the largest enterprise network infrastructure companies in the United States with roughly 500,000 route miles of fiber globally, is an instructive example. By the time Lumen began its modernization program, it was running more than 17 separate inventory systems, ingesting data from nearly 500 sources with no common schema, and managing network hardware spanning four decades of manufacturing generations. That is an extreme version of a problem most large operators recognize.

The operational cost is not abstract. Engineers spend hours correlating data across systems to answer questions that should take minutes. Change management requires weeks of planning because no one has full confidence in what will break. Service delivery slows down because provisioning still involves manual steps across multiple tools. And when something goes wrong on the network at 2 a.m., the time to diagnose and fix it stretches longer than it should.

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What Is an Operations Support System?

An operations support system, or OSS, is the software layer that helps network operators manage their infrastructure. In practice, the term covers a broad category: inventory management (what equipment exists and where), service orchestration (how services are activated and changed), assurance and analytics (is everything working, and how well), and fault management (what broke and why).

Historically, each of those functions was served by a separate product from a separate vendor, each with its own data model and its own integration requirements. A carrier might run one vendor's inventory system, a different vendor's fault management platform, and yet another vendor's provisioning tool, stitched together with custom integrations that became unmaintainable over time.

The phrase "OSS modernization" means replacing or consolidating that fragmented stack with a platform that handles multiple functions on a common data layer. The business case is straightforward: fewer tools, fewer integrations, faster operations, and a foundation for automation. The execution is not straightforward at all. Replacing core operational systems on a live network is exactly as risky as it sounds.

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The Telemetry Problem: Where YANG Push Fits In

Any automation or analytics platform is only as good as the data it receives. Network telemetry — the continuous stream of metrics and state information from network devices — has traditionally been collected by polling. A management system asks each device, on a schedule, to report its current status. On a network with thousands of devices, polling is slow, resource-intensive, and creates a lag between what is actually happening on the network and what the management system sees.

IETF-standardized YANG Push inverts that model. Rather than the collector asking devices for data, devices push updates to the collector, either when something changes (on-change mode) or at a defined interval. YANG itself is a data modeling language that defines the structure of network device configuration and state information in a vendor-neutral way. YANG Push is the subscription mechanism that streams that structured data in near real time.

The practical significance: a management platform receiving YANG Push telemetry knows about a routing change or a performance anomaly seconds after it happens, not minutes later when the next polling cycle completes. At Swisscom, engineers Ahmed Elhassany and Bill Kaufmann of Blue Planet demonstrated this at Upperside 2026, showing how dramatically YANG Push can compress the time between a network event and a management system's awareness of it. That compression is what makes real-time digital twins and closed-loop automation credible rather than theoretical.

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The Digital Twin Concept in Network Operations

A network digital twin is a software model that mirrors the live state of a physical network in real time. The term is borrowed from manufacturing and industrial engineering, where digital twins of machines and production lines have been used for simulation and predictive maintenance for years. In network operations, the concept serves a specific set of use cases.

The most immediate use is change validation. Before an engineer makes a routing change, modifies a policy, or migrates a service, they can run that change through the digital twin to see the predicted impact. If the simulation reveals a problem, the change is modified before it touches the live network. This shifts network change management from a process dominated by caution and slow manual review toward something closer to a software development workflow with a test environment.

A second use case is forensic analysis. When a service disruption occurs and is resolved, operators need to understand what happened and why. A digital twin with historical state data — sometimes called digital video recorder replay in Blue Planet's framing — lets engineers rewind to the moment the disruption began and trace the sequence of events. That capability turns post-incident analysis from a multi-day exercise into something that can be completed in hours.

Blue Planet's Route Optimization and Analysis product builds an IP digital twin that the company claims processes 50M routing entries hourly and delivers 10x faster routing fault isolation. The accuracy of that twin depends directly on the quality and speed of the telemetry feeding it — which is precisely why YANG Push matters to Blue Planet's platform story.

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Blue Planet: What the Company Actually Does

Blue Planet is a software division of Ciena, a publicly traded optical and networking systems company. Ciena acquired the technology through its 2015 purchase of a company called Cyan, which had built one of the first cloud-native network orchestration platforms. That acquisition, valued at approximately $400 million, became the foundation for what is now Blue Planet's intelligent automation portfolio.

The portfolio covers five main areas. Inventory provides a unified view of physical and virtual network assets across multi-vendor environments — the single source of truth that fragmented legacy estates lack. Orchestration automates service activation and lifecycle management across network domains. Unified Assurance and Analytics handles fault and performance management with real-time data. Route Optimization and Analysis delivers the IP digital twin and routing intelligence described above. AI Studio is the newest layer, providing a low-code environment for building and deploying artificial intelligence agents that automate network operations workflows.

The company reached record revenues of $78M in 2024, up 12% year on year. Its most recent quarterly result was $27.8 million, up 2.3%. These are not large numbers relative to the total addressable market, but the growth trajectory and the strategic importance of the OSS modernization wave are what Blue Planet's leadership is pointing to. Joe Cumello, who has led Blue Planet since the Cyan acquisition and serves as Senior Vice President and General Manager, has positioned the division as the platform carrier for the autonomous networks shift.

Blue Planet's primary competitive claim is vendor neutrality. Because Ciena's core business is optical transport rather than IP routing hardware, Blue Planet can credibly argue that its orchestration and analytics software is not quietly optimized for any particular vendor's gear. That matters to carriers running multi-vendor networks, which is essentially every carrier at scale.

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The Competitive Landscape

The vendors competing in this space divide into three groups, each approaching from a different position of strength.

Vendor	Core Platform	Competitive Position	Key Tension
Blue Planet / Ciena	Intelligent Automation Portfolio, AI Studio	Multi-vendor neutral, optical-layer integration, cloud-native OSS	Ciena hardware ownership complicates neutrality claim; slow sales cycles
Cisco Crosswork	Network Services Orchestrator (NSO), Crosswork Network Controller	Enormous installed base, deep carrier relationships, strong developer ecosystem	Primary hardware vendor; multi-vendor neutrality credibility gap
Ericsson / Nokia	OSS portfolios, Network Services Platform	Decades of telco relationships, deep protocol support	Also hardware vendors; face same neutrality challenge as Cisco
Itential	Itential Automation Platform	Fast to deploy, developer-friendly, proven at scale (Lumen: 200M+ jobs/month)	Point solution; lacks full-stack OSS depth
Kentik	Network Observability Platform	Strong on traffic analytics and internet visibility	Observability specialist; limited orchestration capability
AWS / Google Cloud	Cloud-native network management tooling	Infrastructure at scale, AI integration, hyperscaler relationships	Long-term structural threat; carriers increasingly run workloads on public cloud

Cisco deserves particular attention because the competitive dynamic is not simple opposition. Cisco's Crosswork Network Services Orchestrator claims the same multi-vendor automation story as Blue Planet, with support for over 1,000 third-party physical and virtual devices and a mature developer ecosystem. The difference is structural: Cisco's core revenue comes from selling routers and switches. Carriers running significant Cisco infrastructure are in conversations with Cisco about automation by default. Blue Planet has to earn its way into those conversations against that relationship advantage.

At the same time, Cisco is actively building agentic artificial intelligence workflows into Crosswork using open standards including OpenConfig and YANG-based protocols — the same standards space Blue Planet occupies. Neither company is standing still.

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The Lumen Case: What a Real Deployment Looks Like

Lumen Technologies is the most instructive current Blue Planet deployment to examine, both for what it reveals about the platform's potential and for the complexity it exposes.

Lumen completed a financial turnaround in early 2026 and announced a multi-year growth plan targeting approximately 58 million fiber miles by 2031, with nearly $13 billion in private connectivity fabric contracts including AI infrastructure companies. That growth plan requires a network operations capability that Lumen's legacy estate, with its 17-plus inventory systems and 500 data sources, cannot support. The Blue Planet AI Studio deployment, announced in February 2026, is a direct response to that operational constraint.

Initial use cases include device model generation — automating the process of building accurate digital representations of network devices — and digital network twin operations. Lumen's own description of the underlying data challenge is worth understanding: the company ingested nearly 500 data sources into a common platform and built data objects linking network elements, customer services, cost data, and revenue data across what were previously hard organizational and system boundaries. That data foundation is what makes AI agent deployment meaningful. Without clean, unified data, AI agents have nothing reliable to act on.

The complexity worth noting: Lumen also runs a separate orchestration platform from Itential, processing over 200 million automation jobs and tasks per month across more than 50 unique systems. Blue Planet AI Studio is additive to that existing automation layer, not a replacement for it. That means Lumen is running a multi-vendor automation stack, which raises a legitimate question for anyone evaluating these platforms: platform consolidation is the stated goal, but the reality for large operators is often continued multi-vendor complexity even after a modernization program begins.

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Who Actually Buys This

The primary buyers are Tier 1 and Tier 2 carriers: national and regional telecom operators with multi-vendor, multi-domain networks and a business case for reducing operational expenditure through automation. Swisscom, Telefónica Germany, and Lumen are representative of this profile.

Beyond traditional carriers, the buyer universe is expanding. Cable operators, called multi-system operators in industry terminology, are under pressure to automate fiber and hybrid fiber-coaxial network operations as they compete with telcos on broadband. Large enterprises running private wide-area networks at significant scale face the same multi-vendor complexity problem. And hyperscale infrastructure operators — the companies building data center networks to support artificial intelligence workloads — need the same kind of real-time telemetry and automation capability, though they tend to build more of it themselves.

The organizations that do not fit Blue Planet's profile well are smaller operators with relatively homogeneous, single-vendor networks. The integration complexity and implementation cost require scale to justify. Blue Planet counts more than 200 deployments worldwide, which indicates meaningful market penetration, but also suggests significant room to grow in a global carrier market with thousands of operators.

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The Autonomous Networks Direction

The destination that Blue Planet and its competitors are collectively pointing toward is what the telecom industry calls autonomous networks: infrastructure that can detect conditions, make decisions, and take corrective action without human intervention. The TM Forum, an industry standards body, defines autonomous network maturity across five levels, from fully manual operations at level zero to fully self-optimizing networks at level five. Most large carriers today are operating somewhere between level one and level two.

The path from where most carriers are today to meaningful autonomy runs through three requirements: accurate real-time data (the telemetry layer, where YANG Push matters), unified network intelligence (the OSS consolidation and digital twin layer, where Blue Planet competes), and action capability (the orchestration and AI agent layer, where AI Studio and its competitors are building). None of those three requirements can be skipped. A carrier with excellent telemetry but fragmented inventory data cannot build a reliable digital twin. A carrier with a digital twin but no orchestration capability can analyze but not act.

Blue Planet's bet is that by building a platform covering all three layers with a common data foundation, it can become the operational system of record for carriers on the journey toward autonomy. The competitive risk is that carriers piece together best-of-breed solutions across each layer, using Itential for orchestration, Kentik for observability, and Blue Planet for something specific — the integration platform story dissolves into a point solution story.