At Netopt.Design, we believe smarter network design starts with strategic insight. Our whitepapers explore how telecom networks can evolve to meet next-generation demands—from multi-layer architecture to AI workload optimization. These are written for CTOs, planners, and technology leaders seeking more efficient, future-ready infrastructure.
1️⃣ AI and the Future of Network Design: A Comprehensive Evolution from SONET to ROADM
Understand how telecom networks have evolved over two decades—from TDM-based SONET/SDH transport to IP/MPLS over DWDM and ROADM-based designs. This paper details major shifts driven by ecommerce, video, and AI, and outlines how planning tools have evolved to address these networks and services.
- History of transport evolution across North America
- Traffic growth impact from video, cloud, and AI
- Evolution of network planning tools
2️⃣ NetOpt: Bridging the Multi-Layer Network Planning Divide
This whitepaper introduces Netopt as a unified planning platform that eliminates the silos between IP/MPLS and optical network design. Learn how legacy tools fail to coordinate across layers—and how Netopt delivers substantial savings by modeling everything from fiber and latency to MPLS path constraints and CDN hierarchy.
- How margin stacking inflates network capacity
- Why existing tools miss reuse opportunities
- Netopt’s brownfield-aware, SLA-driven optimization approach
3️⃣ Optimizing AI Traffic Over WAN: How NetOpt Meets Next-Generation Demands
AI workloads are reshaping how wide-area networks must perform. This paper explains how Netopt supports AI training and inference across distributed fiber-connected data centers, using latency-aware, multi-path designs to optimize performance and resilience.
- Designing latency-sensitive WAN paths for AI training
- Connecting global data centers for distributed inference
- How Netopt models SLA, cost, and performance trade-offs
4️⃣ Optimizing Data Center Networks with NetOpt.Design
As data center traffic surges—especially from AI workloads—traditional leaf–spine designs are being pushed to their limits. This paper shows how NetOpt.Design enables smarter leaf–spine scaling, optical integration, and AI‑ready latency guarantees to deliver cost‑effective, future‑proof fabrics.
- Scale leaf–spine fabrics with additional super‑spine tiers
- Evaluate the benefits of optical spine and core layers
- Enforce strict latency caps for model‑parallel AI traffic while balancing cost elsewhere
- Plan capacity with demand‑aware and statistical traffic engineering