BBlue Planet AI Studio by Ciena

Lumen Technologies said on February 19, 2026 that it would use Blue Planet AI Studio to build, manage and run AI agents across several network domains, starting with device model generation and a digital network twin. For a buyer, that is the headline: a publicly listed US network operator chose Ciena’s Blue Planet division, rather than a general-purpose AI platform, to put agents inside the operations support systems that track every device, circuit and service on its network.

Blue Planet AI Studio is best for service providers and large network operators that already run, or plan to run, Blue Planet’s inventory and orchestration software and want agents for device modeling, inventory reconciliation, service ordering and incident resolution. Results so far are mostly described as expected outcomes rather than measured numbers, and pricing is shared privately, so published results would help buyers. It is sold on custom quotes, and we rate it 7.8/10 on our scale. We have not used AI Studio ourselves; this review is based on Blue Planet, Ciena and Lumen announcements, an MWC 2026 technical post on the AWS work and Gartner Peer Insights reviews.

A Short Record of Confirmed Facts

Blue Planet’s agentic AI is new, so the record is short. These are the facts we confirmed on the source pages.

The Lumen deal is the fact that matters most. Device modeling sounds dull, but new equipment types typically have to be modeled before inventory and orchestration systems can use it, and that work has traditionally been done by hand. If an agent can produce those models, new equipment reaches service sooner and inventory stays accurate.

Both sides framed the deal around cost and operations. Kye Prigg, Lumen’s chief commercial operations officer, said the platform enables AI agents that simplify operational tasks and cut costs. Joe Cumello, senior vice president and general manager of Blue Planet, said the agents would speed the move toward fully autonomous networks. Lumen also plans to use agentic AI in its digital network twin operations model to get proactive, real-time network insight, which suggests the relationship is meant to grow beyond device modeling.

Neither Lumen nor Blue Planet has published hard numbers yet. The release describes expected outcomes, and the TM Forum Catalysts are industry proof-of-concept projects rather than commercial deployments. Ask for measured results from Lumen’s first use cases before committing to a wide rollout.

An Agent Layer on Cloud-Native OSS

Blue Planet sells cloud-native OSS software that helps service providers automate network and service operations across vendors and domains. AI Studio adds an agent layer on top of that OSS data.

AI Studio

AI Studio is a low-code, OSS-native environment. Network operations teams use it to design, deploy and manage agents that run inside OSS workflows, combining the agents with contextual OSS data such as inventory, topology and service records. Results feed closed-loop workflows, so an agent’s output can trigger the next automated step. Blue Planet ships prebuilt OSS agents to speed adoption and connects AI Studio to its Blue Planet IDE.

Equipment Modeler, Reconciliation and Other Agents

• Equipment Modeler Agent: creates vendor-specific device models that can be provisioned into Blue Planet Inventory.
• Device reconciliation agent: matches devices discovered on the network with what the inventory says is there.
• Schematic generation agent: produces network schematics.
• Intent translation agent: turns a customer’s service intent into orders.
• Resource forecasting agent: forecasts the network resources services will need.
• Incident resolution agent: investigates and resolves incidents, including SLA degradation.
• Supervisor agent: coordinates the specialist agents across a job.

Hosted on AWS

For operators that do not want to host everything themselves, Blue Planet offers Agents-as-a-Service: centrally hosted agents that planners, designers and operations teams consume. The Equipment Modeler Agent runs in an Amazon Bedrock Agents tenancy, and AWS AgentCore handles scaling. At MWC 2026 the two companies showed AI Studio stitching services across domains using AWS-native AI services.

Level 4 Autonomy Shown at DTW Ignite

At DTW Ignite in June 2026, Blue Planet showed a Level 4 autonomy architecture that covers the service lifecycle from intent-based creation to fulfillment and Day 2 operations, using closed-loop automation to watch SLAs, predict issues and fix faults with minimal intervention. It also showed an AI-driven digital twin that simulates network conditions and adjusts paths to protect service quality.

Blue Planet’s industry projects hint at the next use cases. In the TM Forum Agentic Network Growth Engine Catalyst, KDDI and LGU+ worked with Accenture and ServiceNow on agentic AI, digital twins and shared data platforms for zero-touch operations and API-driven revenue models. In The Big Deal Phase II, Orange, Indosat, Vodafone and Spark worked with Infosys and CSG on intent-driven quoting, AI-assisted catalog modeling and automated ordering for enterprise services. Blue Planet also showed a new offering for configuration, change and lifecycle management across multi-vendor networks at the same event.

Operators Keep Control of Which Agents Run

Blue Planet frames the prebuilt agents as a way to speed adoption while operators keep operational control. Teams still decide which agents to run, review models and orders the agents produce, and set how far closed-loop actions may go. Building custom agents in AI Studio is low-code, but it still needs people who understand the OSS data model.

Negotiated Contracts With Service Providers

Blue Planet does not publish prices for AI Studio or its agents. Contracts are negotiated with service providers.

Sizing Device Onboarding for 200 New Models

With no public prices, the useful exercise is sizing the work the agents replace. The volumes below are our own illustrative assumptions.

• Device onboarding: an operator adding 200 new device types a year, at two days of engineer time to model each by hand, spends about 400 engineer days a year on modeling. That is the pool of work the Equipment Modeler Agent targets.
• Inventory reconciliation: if 5% of 100,000 inventory records drift from the live network each quarter, that is 5,000 records to check, the job the reconciliation agent is built for.
• Hosted agents: the as-a-service model swaps some in-house hosting for AWS usage charges, which grow with how often agents run.

Costs to plan for beyond the license: Blue Planet OSS itself if you do not already run it, AWS consumption for hosted agents, data cleanup before agents can trust inventory records, and staff time to review agent output during rollout.

Blue Planet AI Studio Compared With Nokia Autonomous Network Fabric, Amdocs aOS and Totogi BSS Magic

Telecom agent platforms divide by where they sit: network equipment, OSS, or BSS. Blue Planet is the OSS option.

Pick Blue Planet when inventory accuracy, device onboarding and service orchestration are the bottleneck. Pick Nokia when the work is in radio and transport assurance, and Amdocs or Totogi when the pain sits in orders and billing. Large operators may end up with more than one. For an enterprise view of network AI, see Ericsson NetCloud Assistant, and browse the full list in our AI agents for telecom guide.

Blue Planet OSS Users Onboarding New Equipment

• Existing Blue Planet OSS customers: agents work directly on the inventory and orchestration data you already have.
• Operators onboarding lots of new equipment: the Equipment Modeler Agent targets the manual work of building device models.
• Teams fighting inventory drift: the reconciliation agent compares discovered devices with records.
• Operators building toward higher autonomy: the Level 4 architecture and digital twin show where the platform is heading.
• Operators on AWS: the hosted Agents-as-a-Service model runs on Amazon Bedrock Agents and AgentCore.

Small ISPs and Care or Billing Teams

• Small ISPs: the product is sold to service providers on negotiated contracts.
• Teams focused on customer care or billing: the agents target network operations.
• Operators heavily invested in another OSS stack: much of the value comes from Blue Planet’s own inventory and orchestration.
• Teams wanting a general agent builder: AI Studio is shaped around OSS data and network workflows, not general business tasks.
• Buyers who want proof in numbers first: published outcomes are mostly expectations so far, and measured results from early deployments would help.

Expected Results Versus Measured Ones

• Expected versus measured results: the Lumen release describes expected outcomes, and TM Forum Catalysts are industry demonstrations.
• OSS dependency: agents are designed around Blue Planet’s own OSS data model and inventory.
• Data quality: agents that reconcile or model inventory rely on clean records; budget for cleanup.
• Cloud costs: the hosted model adds AWS charges that rise with use.
• Small review base: Blue Planet has 4 ratings on Gartner Peer Insights, all positive, and more reviews would give buyers a fuller picture.

TM Forum Catalysts and DTW Ignite 2026

• On June 10, 2026, Blue Planet said it would show agentic AI and a Level 4 autonomy architecture at DTW Ignite 2026, alongside TM Forum Catalysts with KDDI, LGU+, Orange, Indosat, Vodafone and Spark.
• At MWC 2026 in March, Ciena demonstrated Blue Planet AI Studio at the AWS booth, and Blue Planet detailed its Agents-as-a-Service model on AWS.
• On February 19, 2026, Blue Planet announced that Lumen will use AI Studio and AI agents for device model generation and digital network twin operations.

Credible for Operators Choosing an OSS With Agents

For a service provider that runs Blue Planet OSS, or is choosing an OSS and wants agents built into it, AI Studio is a credible option with a named major customer and a clear set of prebuilt agents. It scores 7.8/10 on our scale: good on autonomy and integration, and the score would rise with published pricing, a larger review base and measured outcomes in place of expectations.

The best way in is a narrow use case with a measurable baseline, such as device modeling time or inventory mismatches, as Lumen chose. Measure it for a quarter, then decide whether to extend agents into orchestration and incident resolution.

AI Studio Terms and the Agents-as-a-Service Model

How Much Does Blue Planet AI Studio Cost?

Blue Planet does not publish prices. AI Studio, its agents and the hosted Agents-as-a-Service model are sold on negotiated terms, and hosted agents add AWS usage costs.

Do I Need Blue Planet OSS to Use AI Studio?

AI Studio is built as an OSS-native environment, and several agents, such as the Equipment Modeler, write into Blue Planet Inventory. Operators on other OSS stacks should confirm which agents work without Blue Planet’s inventory and orchestration.

What Is the Equipment Modeler Agent?

It creates vendor-specific device models that can be provisioned into Blue Planet Inventory, a task usually done by hand when operators add new equipment. In the hosted model it runs in an Amazon Bedrock Agents tenancy.

Who Uses Blue Planet AI Studio?

Lumen Technologies announced in February 2026 that it is adopting AI Studio and agents across its network operations. Blue Planet has also joined TM Forum Catalyst projects with operators including KDDI, LGU+, Orange and Vodafone.

Which Jobs Sit Outside Blue Planet AI Studio?

It does not handle customer care or billing, and it is not a self-serve tool for small providers. Its agents depend on accurate OSS data and on the limits operators set for closed-loop actions.