Aviz Networks expands AI networking software with new funding
Aviz Networks focuses on updating networking software to meet the changing needs of data centers and edge networks integrating Artificial Intelligence (AI). The company provides vendor-neutral software solutions based on the Community SONiC platform, improving network transparency and incorporating AI-driven management tools.
Aviz's software enables operational flexibility and control across various hardware options, which can lead to cost reductions. Its products have been implemented by organizations including online retailers, telecommunications firms, GPU-as-a-service providers, cloud providers, and assorted enterprise networks.
The company's AI Networking Stack offers capabilities such as Network Operations with orchestration, monitoring, real-time alerts, performance tracking, and Remote Direct Memory Access (DMA) (RDMA) over Converged Ethernet (RoCE) networks. It also enhances network visibility through Packet Brokers and Service Nodes and supports a vendor-neutral data lake that powers an AI assistant called Network Copilot™. The solutions integrate with a broad range of hardware components including ASICs, switches, GPUs, DPUs, and servers.
Aviz has undertaken activities intended to expand the deployment of these AI networking technologies and plans to extend its reach into additional market areas. This includes the recent completion of a funding round expected to support growth and exploration of new client sectors.
Vishal Shukla, CEO of Aviz Networks, said, “Traditional networking solutions, even the best, struggle to adapt as infrastructure increasingly depends on AI and data-driven applications. A vendor-agnostic approach is crucial to advance networks to the next level. This strategy leverages top-tier networking hardware, a robust network operating system designed for AI, and end-to-end networking tooling that integrates AI directly into everyday networking. Aviz has perfected this approach, placing AI at the heart of how networks are built and managed. This funding round will boost our growth in current markets and allow us to explore new verticals, strengthening our commitment to innovation and excellence in an AI-driven era. We are excited to welcome new investors and deeply appreciate the ongoing support from our existing investors, partners customers.” Louis Toth, co-founder and managing partner of Alter Venture Partners, said, “Aviz is redefining what is possible in the networking space with its AI-driven, vendor-agnostic solutions. Alters investment in Aviz is a testament to our belief in the teams vision to transform and ameliorate network management and operations. We are particularly impressed by the companys technological differentiation and the strong partnerships its management team have forged with key ecosystem players to help the customers navigate this transition. The co-founders visionary approach not only sets Aviz apart in the industry but also aligns perfectly with our funds investment thesis of backing leading start-ups that are using AI to transform cloud and edge infrastructure.” Gavin Cato, head of portfolio solutions and CTO at Celestica, said, “Aviz's innovative approach transforms how companies build and deploy network infrastructure for data centers and the edge, enabling them to evolve and integrate AI opportunities. Were proud to collaborate with Aviz as they work towards achieving their vision.” Quinn Li, senior vice president at Qualcomm Technologies and global head of Qualcomm Ventures, said, “As networks evolve, embracing AI will be crucial for enabling superior performance and operational excellence. By integrating AI with open-source solutions like SONiC, Aviz Networks is empowering enterprises to build scalable and flexible networks in a cost-effective manner. We are excited to support Aviz Networks to transform enterprise networking.”
The company described plans to continue developing solutions that embed AI at the core of network management and to broaden its engagement with various client types as it progresses.