Multi-Domain Service Orchestration, Agent-Based Provisioning, & Spec-Driven Development Across SD-WAN, IP/MPLS, and Branch Connectivity Domains
Manual, multi-domain service provisioning across SD-WAN, IP/MPLS, and branch connectivity required deep per-controller expertise, slowed activation, and could not be safely opened to AI-driven execution without governance, audit, and human-in-the-loop controls.
Itential FlowAI and the Itential Platform provided a unified orchestration layer where the architecture team could build goal-based agents, deterministic workflows, and end-to-end multi-domain service flows – with the same governance applied to AI and human actions.
Chosen for the deterministic-plus-agentic execution model, native multi-controller integration, Spec-Driven Development, and platform-level governance that let agents act on real infrastructure with auditability, approval gates, and policy controls built in.
A Tier-1 communications service provider operates across consumer, enterprise, and wholesale markets, delivering connectivity, SD-WAN, and managed services across multiple countries and customer segments.
As enterprise demand for hybrid connectivity grew, the architecture team faced a familiar problem: every new service required orchestration across multiple controller domains, each with its own API surface, service model, and operational pattern. Provisioning a single customer service often meant coordinating actions across multiple SD-WAN platforms, an IP/MPLS service orchestrator, and branch connectivity infrastructure – with manual handoffs, custom integration code, and engineer-intensive validation between each step.
The team had built strong internal automation. But scaling that automation across new services, new controllers, and new customer segments meant rebuilding integration logic each time. And as AI entered the conversation, leadership needed a way to introduce agent-driven execution without giving up the governance, traceability, and control their enterprise customers required.
Each gap blocked the path to scaled automation – and made it impossible to safely introduce AI on top.
Service activation across SD-WAN, IP/MPLS, and branch connectivity required deep familiarity with each controller’s service models, API conventions, and execution patterns. Engineers had built integrations that worked – but maintaining them, extending them, and onboarding new domains required engineering bandwidth the team did not have.
Adding agentic AI raised harder questions: how would agents know which tools to use, how would the team prevent runaway execution, and how would they audit what an agent did, who approved it, and what it changed? The team needed AI reasoning without losing the governance and predictability that made automation safe in the first place.
The team was thinking past the demo: token consumption per run, which agents could be safely converted to deterministic workflows once their patterns stabilized, and how to govern what tools agents could access at build time versus runtime. A deployment readiness question, not a curiosity one.
Rather than watch a vendor demo, the architecture team asked for four working days, access to the platform, and Itential’s team in a support role – not leading. Several criteria shaped the decision.
Six capabilities sat at the center of the decision – together giving the team a governed foundation for both deterministic execution and agentic operations.
AI agents can only act responsibly when they have a governed, deterministic execution layer beneath them. Itential provides exactly that – well-defined, auditable workflow execution that AI can invoke reliably, with policy enforcement and access controls built in. For the team, this was not just an automation requirement. It was the prerequisite for agentic operations.
The Itential Platform integrated with multiple SD-WAN controllers, the IP/MPLS service orchestrator, and branch connectivity infrastructure through native API ingestion – with the same integration model exposed as tools to FlowAI agents. Agents could reason across multiple controller domains, including across competing controllers in the same domain, without custom integration code per service.
Itential’s published Claude skills allowed architects to define agent intent in plain language, then watch the system check feasibility, design the solution, build the agent, self-test it against the live environment, and document what it learned – including its own deviations and corrections.
Enterprise governance – RBAC, audit logging, secrets management, approval workflows, SSO – applied natively to agent execution, not bolted on after the fact. Every agent action was traceable, every change auditable, every approval recorded.
The platform exposed per-step token consumption for each agent execution, giving the team the foundation to track agent cost over time, identify high-cost agents, and convert stabilized patterns to deterministic workflows when appropriate.
Approval gates could be inserted at any point in agent execution, with the option to route approvals through change management systems the team already used. Agents could draft, validate, and stage changes – but humans approved them.
Over four working days – supported, not led, by the Itential team – the architecture team built five working FlowAgents, multiple deterministic workflows stitching them into end-to-end service flows, and a Spec-Driven Development build that delivered a working agent in under fifteen minutes.
A deterministic workflow crossed three controller domains in a single execution – IP/MPLS service activation, branch site provisioning, and SD-WAN customer creation combined into one customer service.
Five FlowAgents spanning SD-WAN customer creation, branch site provisioning, multi-domain L3VPN activation, configuration compliance, and day-two operations – built around customer outcomes rather than per-controller tasks.
One architect stated intent in plain language. The system asked clarifying questions, generated a spec, validated feasibility, designed the solution, built the agent, self-tested against the API, hit a permissions error, self-corrected, and delivered a working agent – fully documented – in under fifteen minutes.
Per-run token consumption visibility, build-time tool selection, RBAC, audit trails, and human-in-the-loop approvals – applied to every agent and routed through the team’s existing change management process.
The engagement validated that agentic operations could be deployed in a production-grade telecommunications environment – without the months-long integration cycles required by traditional approaches, and without trading off the governance enterprise customers require.
See how Itential connects AI reasoning to governed execution across your entire infrastructure.