Aviz Networks unveiled its Networking 3.0 Stack, a suite including ONES for network operations, OPB for Packet Brokers, and its new GenAI-based conversational Network Copilot. With this stack Aviz offers comprehensive vendor agnostic solutions spanning Data Centers, Edge Networks, and AI Fabrics.
The Networking 3.0 Stack features compatibility across multiple ASICs, switches, NOS, clouds, and LLMs, and empowers network owners with choice and control enabling dramatic cost savings.
Aviz said its new Network Copilot, which is available for on-premise and AWS deployments, can integrate into pre-existing data lakes or can generate its own data lake while keeping data ownership with customers. In its initial release, Network Copilot . Network Copilot leverages open source LLMs and enables customers to stay abreast of the latest developments in the Generative AI domain.
Utilizing Network Copilot, clients have the capability to pre-train models tailored to their network benchmarks, facilitating ongoing model refinement and adjustment using live data from their networks. This methodology opens up various possibilities, including enhancing network operations, ensuring regulatory compliance, optimizing capacity planning, and beyond. Moreover, clients are provided with the chance to engage with the Aviz Prompt Engineering team to delve into and cultivate novel, previously unexplored applications, thereby pushing the frontiers of innovation in network management.
“With the launch of Network Copilot we have delivered on our vision for enabling open, cloud and AI first networks using a data centric Networking 3.0 stack. Our products enable customers to standardize their NOS, NetOps, Network Data and AIOps layers, giving them the control they need to enable vendor choice while creating long term value,” said Vishal Shukla, CEO for Aviz Networks. “Network Copilot is designed to eliminate entry barriers for network professionals to integrate GenAI into their daily jobs. Network Copilot provides network architects, managers and executives with the ability to work with GenAI technology, laying the path for them to be future GenAI leaders.”
