Aviz Networks announced the completion of its Networking 3.0 Stack, a suite including ONES for network operations, OPB for Packet Brokers, and the 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.

Network Copilot 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 is available for on-premise and AWS deployments. Network Copilot leverages open source LLMs and enables customers to stay abreast of the latest developments in the Generative AI domain.

With Network Copilot, customers can pre-train models for their own network benchmarks, and allow continuous model training and fine-tuning with real-time data from their networks. This approach unlocks potential use cases such as improving network operations, ensuring compliance, optimizing capacity planning, and more. Furthermore, customers have the opportunity to collaborate with the Aviz Prompt Engineering team to explore and develop new, as yet undeveloped use cases, pushing the boundaries of network management innovation.

“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.”