Eighteen Years of Global Networking Expertise, Now Powering the AI Era
Since establishing its Hong Kong headquarters in 2008, Cypress Telecom Limited ("CypressTel") has spent 18 years building deep expertise in enterprise networking, evolving into a globally recognised SD-WAN specialist. Over this journey, CypressTel has served tens of thousands of mid-to-large enterprises, deploying 140+ PoPs and 30+ data centres worldwide to underpin a mature, high-performance cross-border network infrastructure and managed operations capability.
A Milestone Moment at MWC Shanghai 2026
MWC Shanghai 2026 marked CypressTel's debut at a domestic MWC exhibition — and it was anything but a quiet entrance. In an exclusive interview with C114 Communications Network, CypressTel CEO Connee Zhang described the occasion as a "coming-of-age" moment for the company.
At the event, CypressTel officially unveiled its new brand positioning: Global AI Computing and Network Infrastructure MSP — and simultaneously launched a three-tier AI product series spanning the model, network, and computing layers, marking a decisive, full-scale commitment to the AI era.
Seizing the AI Compute Opportunity: Three Product Launches in One Move
The AI computing industry is entering a phase of exponential growth. Industry data indicates that global computing capacity reached 2.1 ZFLOPS (zetta floating-point operations per second) in 2025, and is projected to surpass 16 ZFLOPS by 2030 — a more than tenfold increase over seven years, with a CAGR of approximately 40%. Intelligent computing is the core engine of this expansion, forecast to account for over 80% of total compute demand by 2026.
Building on 18 years of infrastructure expertise and proprietary technology, CypressTel has launched three core AI computing-network products, all validated in real-world production environments. The AI Gateway has already entered a limited commercial deployment phase.
1. AI Gateway — Unifying Enterprise AI Access
The AI Gateway is CypressTel's first fully deployed AI infrastructure product, purpose-built to solve the fragmented, complex, and costly challenge of managing multiple large language models (LLMs) across an enterprise.The platform aggregates more than 50 mainstream LLMs — including ChatGPT, DeepSeek, Qwen, and Kimi — into a single unified access layer, supporting one-stop invocation and centralised token-based billing. A cross-model memory capability enables seamless context continuity when switching between models, significantly enhancing AI application performance. The product also supports private deployment with on-premises data retention, ensuring enterprise-grade information security. In a live deployment at a leading online professional education platform, the AI Gateway reduced AI operations workload by 70% and improved student AI-assisted tutoring satisfaction by over 20%.
2. AI-Ready High-Bandwidth SD-WAN — Purpose-Built for LLM Training and Inference
ModelNet is CypressTel's network product specifically engineered for large model training and inference scenarios, directly addressing the industry's most CypressTel's AI-Ready High-Bandwidth SD-WAN is a network product specifically engineered for large model training and inference scenarios, directly addressing the industry's most common bottleneck: "sufficient compute, insufficient network."[1][5] Powered by CypressTel's 10T-class global backbone network, it supports single-link bandwidth exceeding 100G, with cross-regional transmission latency controlled within 20ms. Intelligent traffic scheduling and dynamic bandwidth allocation make it fully compatible with the high-throughput, low-latency demands of AI training and inference workloads. A leading domestic new energy vehicle manufacturer's autonomous driving team has commercially deployed the product. Prior to adoption, the enterprise's cross-city links experienced latency exceeding 200ms and packet loss rates above 5%, severely impacting training stability. After migrating to the dedicated private network, latency dropped to under 35ms, packet loss approached zero, and model training efficiency improved by 40%. The company has since migrated all cross-data-center training traffic to this private network.
3. GPU Computing Services — Completing the Full-Stack Infrastructure
CypressTel's GPU Computing Services address the compute layer, offering a full range of GPU resources including bare metal, virtual machines, and container-based environments, covering mainstream GPU models including H100, H200, B200, and GB200. The service supports hourly billing and elastic scaling, making it ideally suited for tidal compute demand patterns.[6][3] A top-tier short-video platform has deployed GPU Computing Services for its AI content moderation workloads, leveraging elastic scaling to adapt to overnight peak loads and daytime low-usage periods. The result: overall computing costs reduced by 30%, with all business data transmitted exclusively over CypressTel's private backbone network — substantially enhancing data security and eliminating exposure to public internet risks.
Brand and Business Transformation: From Traditional Networking to AI ComNet
"CypressTel has spent 18 years in enterprise networking and SD-WAN — so why make the shift to AI computing networks?" In addressing this question from C114 and industry peers, CEO Connee Zhang was candid: the transformation is driven equally by customer demand and long-term strategic vision.
Before 2023, over 90% of CypressTel's client requirements centred on traditional global networking services — primarily cross-border interconnection for enterprises expanding overseas and multinational organisations, with the focus squarely on low-latency, low-packet-loss, cost-efficient network transport.
From the second half of 2024, the accelerating commercialisation of large language models triggered a fundamental shift in client requirements. Enterprises were no longer satisfied with basic network transmission. They faced entirely new challenges: supporting the high-bandwidth demands of LLM training and inference, managing cross-regional model instability, handling fragmented multi-model billing, and ensuring data coherence across systems. Market demand evolved from single-service networking to integrated, full-chain solutions spanning network, compute, and AI models — a standard that traditional SD-WAN alone could no longer meet.
CypressTel had already been building toward this transition. In 2024, the company co-established an SD-WAN joint innovation laboratory with Huawei and was approved as a Guangdong Province Network Security Intelligent Computing Engineering Technology Research Centre. In 2025, CypressTel launched the OneSight AI Intelligent Operations Platform, enabling automated network fault detection and resolution. By early 2026, the AI Gateway had completed multiple rounds of internal testing with dozens of flagship clients and three major version iterations, achieving full production-ready maturity.
CypressTel's brand evolution mirrors its strategic progression: from "Global SD-WAN Networking Expert" in 2024, to "Global SD-WAN Secure Networking Leader" in 2025, and now to the full commitment to "Global AI Compute and Network Infrastructure MSP" in 2026. This is not a conceptual rebranding — it represents a complete overhaul of technology architecture, product portfolio, and service model, grounded in 18 years of global networking, network security, and intelligent operations expertise, and guided by the real-world demands of LLM training, inference, and multi-AI application orchestration.
Staying True to Infrastructure: Building an Open AI ComNet Ecosystem
Throughout the interview, CEO Connee Zhang emphasised a consistent principle: CypressTel has no intention of disrupting the AI industry or competing with large model vendors or cloud providers.
"Our positioning is clear. We are an AI Global computing and network infrastructure MSP. LLM vendors focus on building better models. Cloud providers focus on building larger compute pools. We focus on building the network layer that makes it all flow — so that computing power can move as freely and reliably as water or electricity, and enterprises can access AI more conveniently, cost-effectively, and securely."
Looking ahead, CypressTel is focused on three priorities:
Accelerating product deployment: Full commercial availability of the AI Gateway is planned for Q3 2026, with continued expansion of AI-Ready High-Bandwidth SD-WAN options and GPU Computing Service configurations.
Deepening R&D investment: Continued focus on AI network optimisation, intelligent compute scheduling, and data security — reinforcing CypressTel's technical differentiation.
Expanding ecosystem partnerships: Deepening collaboration with carriers, cloud providers, and LLM vendors to build an open, mutually beneficial AI infrastructure ecosystem.
Connee acknowledged that the AI computing network market remains in its early stages, with industry standards still maturing and market development ongoing. CypressTel's approach is deliberate and product-first — not chasing scale at the expense of quality. The company's core target for 2026 is to bring its AI Infrastructure solutions to more than 100 enterprise clients across finance, manufacturing, education, and the internet sector, helping each accelerate their AI-driven digital transformation.
Eighteen Years of Foundation. The AI Chapter Begins.
From 18 years of traditional enterprise networking to a comprehensive AI computing and network infrastructure strategy, CypressTel's transformation is rooted in long-term technology investment and guided by genuine market needs.
Standing at this new starting point, CypressTel will uphold its role as a trusted AI infrastructure provider — continuously refining its full-stack product capabilities, strengthening its industry ecosystem, and delivering a stable, efficient, and secure infrastructure foundation that powers the large-scale adoption of AI across every sector and drives the high-quality growth of the intelligent computing industry.
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