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Aviz Networks introduced Network Copilot (NCP), their private AI platform built for NetOps, emphasizing their vision of “Networks for AI, AI for Networks” and enabling open networking with SONiC and LLMs. Aviz Networks, a software networking company founded in 2019, aims to revolutionize networking by separating hardware and software, similar to the server world. Their product portfolio includes Fabric Manager for managing deployments and configurations, an Observability product for deep packet inspection and data correlation, and their flagship Network Copilot. They highlight the widespread issue of data silos and manual workflows in traditional NetOps, which NCP addresses by providing a native language interface to correlate data faster, automate repetitive tasks, and offer recommendations, not self-driving networks.
Aviz Networks highlights that NCP is not a new data lake but rather a tool that bridges existing data islands. It doesn’t require training on an organization’s operational data, as this data is constantly changing and proprietary. Instead, NCP uses an LLM to translate user questions, identify relevant data sources via data connectors, and employ AI agents to process information for a comprehensive answer. A critical aspect of NCP is its private AI platform architecture, ensuring that all data remains local to the customer’s environment, addressing security and privacy concerns. This approach also means the customer controls their LLM instance, without contributing to the training of external models.
NCP is designed to be hardware vendor-neutral, working across various operating systems and hardware platforms, a significant advantage in multi-vendor enterprise environments. Aviz Networks emphasizes that they are not just an LLM company but a networking software company leveraging LLMs to solve real-world network operational challenges. The value proposition lies in its ability to quickly pull and correlate data from disparate tools, offering a more intuitive and faster way to gain insights without the need for data scientists. This significantly reduces the time spent on tasks like compliance reporting and troubleshooting, providing a tangible return on investment for customers seeking to streamline their NetOps.
Personnel: Thomas Scheibe
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