Sep 16, 2025
Marketing Office
Customer
Lyntia Networks is a leading neutral telecom infrastructure provider across the Iberian Peninsula, with operations extending into Europe and North America. It serves both retail and wholesale customers and plays a critical role in enabling digital connectivity across multiple regions.
Situation
Demand for high-capacity connectivity was accelerating across geographies with very different growth curves. Lyntia needed to align technology choices with financial returns and sustainability goals while maintaining operational agility. Vendor TCO claims frequently diverged from real outcomes, fragmenting decision-making and slowing approvals. Siloed data across engineering, finance, procurement, and operations created duplicated work, rework, and delays. Uneven demand made one-size-fits-all deployment models impractical. Energy costs and CO₂ emissions raised ESG requirements and the need for proactive modeling.
Challenges
Escalating network complexity and TCO as vendor models failed to match real-world outcomes.
Inefficient morphology and demand mapping across diverse regions; existing tools lacked flexibility.
Siloed data and fragmented teams (engineering, finance, procurement, operations) driving rework and late decisions.
Delayed investment decisions due to limited techno-economic visibility.
ESG and sustainability pressures to model energy and CO₂ impacts in every plan.
Need for a single, cross-functional solution tailored to Lyntia’s environment, organization, and objectives.
Customer Requirements
Physical asset inventory management (ISP/OSP) with complete visibility and mapping of ducts, fiber, cabinets, passive components, and logical/virtual elements for accurate resource planning and capacity analysis.
Automated network topology discovery and reconciliation to align real-world elements with logical and physical records and reduce discrepancies.
Service lifecycle support and provisioning orchestration to accelerate time-to-market and meet SLAs.
End-to-end service catalogue (CFS↔RFS) to link customer-facing services to resource-facing components for fulfillment readiness and impact analysis.
What Lyntia Implemented with TelcoBrain
Digital Twin and unified ontology capturing technical, financial, and operational parameters in a single, real-time model.
Techno-economic scenario engine with sensitivity analysis to simulate rollout strategies, vendor mixes, and timelines and select profitable, sustainable options.
Cross-team AI assistants for finance, engineering, procurement, and executives, delivering role-aware insights and decisions.
End-to-end inventory intelligence unifying logical and physical layers (CFS/RFS + ISP) to cut reconciliation overhead and enforce a single source of truth.
Central planning cockpit that integrates technology, financial, business operations, and ESG data for “one-pane” decision-making.
Unified service catalogue and service-lifecycle orchestration to speed activation, fulfillment, and SLA compliance.
How Decisions Changed
Work that previously required months across multiple teams could be done in days. Lyntia could ask “what-if” questions on demand—such as a 50% demand surge in a specific region—and immediately see the techno-economic impact. Energy modeling and CO₂ predictions were embedded in every scenario, enabling lower-emission choices when financially viable and keeping expansion aligned with sustainability commitments.
Results
32% TCO savings on the access and aggregation network.
Planning acceleration: from 2–3 months to 1–3 days (also expressed elsewhere as 2 months to 2 days).
Higher efficiency and accuracy for procurement, technical, and financial teams in vendor discussions.
100% accuracy and tracking of multi-vendor assets across physical and virtual elements.
AI-driven productivity: AI agents deployed to technical and non-technical teams, enabling >90% faster analysis and insight generation.
Sustainability impact: optimized TCO with reduced CO₂ emissions and improved reliability; finance gained visibility to cash flow, IRR, and NPV to support confident approvals.
Operational and Financial Impact
Visibility and accuracy: a single source of truth for finance, procurement, engineering, operations, and business units; consistent data across inventory, planning, and execution eliminated rework and planning errors.
Speed and efficiency: planning cycles reduced to days, enabling faster go-to-market, budget cycles, and infrastructure readiness.
Financial performance: 32% TCO savings and stronger ROI confidence through vendor-neutral, lifecycle-based comparisons.
Procurement leverage: independent, AI-assisted vendor benchmarking improved negotiations, contract terms, and lifecycle cost control.
Sustainability and ESG alignment: proactive energy modeling and CO₂ predictions informed every scenario and deployment plan.
Capabilities Mapped to the Original Requirements
Physical/virtual/logical inventory: complete OSP/ISP visibility (ducts, fiber, cabinets, passive) and logical/virtual elements; automated topology discovery and reconciliation remove silos and duplicated effort.
Service lifecycle and orchestration: linking CFS↔RFS to streamline activation workflows, ensure SLA compliance, and perform impact analysis across retail and wholesale.
Scenario modeling and sensitivity analysis: confidence in both technical and economic outcomes across vendor mixes, timing, and network morphology.
Cross-functional cockpit with role-aware AI: planners and engineers get optimal upgrade paths; finance sees cash-flow, NPV, and IRR; procurement benchmarks vendors; executives view trade-offs across financial, operational, and ESG objectives.
3–5 Year Strategic Roadmap (Benefits Enabled)
Enhanced inventory management across physical, virtual, and logical assets, with comprehensive OSP visibility to support multi-region expansion and precise resource planning.
Full lifecycle asset management (deploy, maintain, upgrade, decommission) aligned to financial and sustainability goals via predictive, automated processes.
Streamlined support and vendor management by integrating vendor-specific TCO models with real data, automating compliance and multi-vendor coordination.
Automated topology discovery and reconciliation across layers to break silos and reduce TCO inflation.
Lifecycle-aware techno-economic decision-making to prevent delayed investments, accelerate market opportunities, and improve regulatory alignment.
Unified service catalogue and provisioning orchestration (CFS↔RFS) to accelerate time-to-market and SLA adherence in retail and wholesale.
Proactive vendor/support ecosystem integration with AI modules for performance monitoring, contract management, and automated ticketing—targeting ~10× faster issue resolution across the global network.
Executive Summary
Lyntia moved from siloed, manual, vendor-dependent planning to an AI-driven, integrated, and sustainability-aligned decision framework. With a vendor-neutral Digital Twin, scenario engine, role-aware AI assistants, unified inventory, and service-lifecycle orchestration, Lyntia reduced TCO by 32%, cut planning cycles from months to days, achieved 100% asset tracking across multi-vendor physical and virtual elements, strengthened procurement, embedded ESG in every decision, and gave finance direct visibility to cash flow, IRR, and NPV.
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