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Alkira's Cloud-Native Networking Platform Addresses Enterprise AI Infrastructure Demands

Burstable News - Business and Technology News September 29, 2025
By Burstable News Staff
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Alkira's Cloud-Native Networking Platform Addresses Enterprise AI Infrastructure Demands

Summary

Alkira's cloud-native networking platform enables enterprises to rapidly deploy and scale AI infrastructure while eliminating traditional hardware constraints and operational complexity.

Full Article

Alkira, founded in 2018 by routing expert Atif Khan, has developed a cloud-native networking platform that addresses the infrastructure challenges enterprises face when adopting artificial intelligence technologies. The company's Cloud Services Exchange (CSX) delivers fully managed network infrastructure as a service, enabling organizations to connect AI data centers, cloud environments, remote users, and edge sites through a single interface.

Khan, who previously co-founded SD-WAN pioneer Viptela before its acquisition by Cisco, explained that Alkira's approach fundamentally differs from traditional networking solutions by eliminating hardware dependencies and providing elastic, on-demand connectivity. The platform allows enterprises to provision or decommission network infrastructure in minutes rather than months, with built-in security, visibility, and governance capabilities. Advanced network services including NAT, DNS/DHCP/IPAM, and integrated third-party controls are accessible through simple configuration interfaces.

The company has experienced significant growth since its founding, with revenue increasing more than fiftyfold and the team more than doubling in size. Alkira now serves multiple Fortune 500 companies, each investing over $1 million annually and expanding their usage. This growth reflects a broader market shift toward cloud-native, consumption-based networking models that can support the dynamic requirements of AI workloads.

Enterprise adoption is driven by the platform's ability to extend existing investments into public cloud environments while eliminating operational complexity. Customers benefit from faster time-to-value, integrated security, and end-to-end visibility without the challenges of hardware refreshes or multi-vendor integration. The platform's architecture enables rapid onboarding of new regions, insertion of third-party security services, and real-time analytics for proactive network operations.

Alkira's product philosophy centers on three key principles: maintaining simplicity for customers, making networking consumable as a service, and embracing rapid iteration through fail-fast methodologies. This approach ensures that complex networking environments remain manageable through intuitive interfaces while supporting the agility required in cloud and AI deployments. The company's commitment to customer-centric design has resulted in high customer loyalty and expansion as organizations discover new use cases for the platform.

Looking forward, Khan identifies significant opportunities in addressing what Alkira terms "Slow AI" - the phenomenon where enterprise AI deployments are delayed by inadequate networking infrastructure. Traditional networks often require months of redesign to support large-scale AI workloads, creating friction in digital transformation initiatives. Alkira's platform aims to make AI adoption frictionless by providing networking infrastructure that scales elastically with computational demands while maintaining security and performance consistency.

The evolving enterprise networking landscape presents both opportunities and challenges for Alkira. As AI-centric architectures become more prevalent, demand grows for networking solutions that can seamlessly connect users, applications, and data across diverse environments. However, maintaining innovation pace while ensuring solution simplicity remains critical in a competitive market. Alkira continues to develop its partner ecosystem and enhance platform capabilities to deliver measurable value to enterprise customers navigating the complexities of AI infrastructure deployment.

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