Network Digital Twins Deliver Reliable AI Outcomes

In the realm of artificial intelligence (AI), especially when applied to networking and security, the accuracy and reliability of data are paramount. AI systems are only as good as the data they consume, and for network engineers, feeding these systems with up-to-date and precise information can make the difference between optimal performance and costly errors. Forward Networks addresses this challenge with a sophisticated solution: a network digital twin that forms a mathematically accurate network model by capturing state and configuration data from all packet-pushing devices— L2 to L4 —and the public cloud. The platform is designed for complex enterprise environments with support for >30 hardware vendors, >35 operating systems, >900 OS, and all three major public clouds.

How reliable are AI recommendations?

AI has transformative potential for network operators, from automating complex tasks to identifying potential security threats and enhancing overall operational efficiency. However, a key element that defines AI’s success in these applications is data quality. Low-quality or outdated data can lead to unreliable results, undermining trust and reducing the practical value of AI solutions in a network environment. For AI to truly add value in network operations, it requires current and encyclopedic data that accurately reflects the real-world state of the network.

Forward Networks' digital twin uniquely solves this challenge by creating the only mathematically accurate, always current digital twin of the network. By continuously collecting state and configuration data from network devices and cloud elements, this model ensures that any AI-driven analysis, query, or insight is rooted in an accurate and up-to-date network representation, giving network administrators confidence in the AI recommendations they implement.

Are my AI tool’s recommendations accurate?

Forward Networks' digital twin aggregates data from across the network, capturing the configurations and states of each device at L2 through L4 and in cloud environments. This comprehensive approach means that no part of the network is left unchecked. The collected data is then used to form a model that is mathematically precise, allowing AI to perform its analyses on a foundation that mirrors the network's current state. 

One of the most important aspects of this digital twin is its regular refresh cycle. Rather than relying on static snapshots, Forward Networks regularly collects snapshots to capture changes as they happen. This capability is crucial for network engineers who depend on up-to-the-minute information to make informed decisions, conduct audits, or troubleshoot issues. With the digital twin’s regular updates, network professionals can trust that the data fueling their AI tools reflects the network’s present configuration and status.

How can network engineers benefit from AI?

For network engineers, Forward Networks’ digital twin provides significant practical advantages. Since the data is consistently refreshed, it enables network professionals to implement AI recommendations with the assurance that they are based on the latest network data. 

Furthermore, Forward Networks enhances its Network Query Engine (NQE) with AI-powered features such as code generation, code explanation, and interactive documentation. These tools streamline complex tasks, allowing engineers to focus on strategic priorities rather than manual configuration and compliance checks. Forward Networks' newest feature, AI Assist, lets engineers build network queries using natural language prompts, expanding access to network insights without requiring additional training. 

What does the new era for AI in network operations look like?

By building a digital twin using current network state and configuration data, Forward Networks enables AI to reach its full potential in network operations. With a model that reflects the network's current state, engineers and operators can trust the results produced by AI, knowing they are grounded in accuracy and precision.

Forward Networks’ digital twin is a critical enabler for AI in network management. It ensures that data is accurate and current, creating a dependable foundation for AI applications in networking. This commitment to data quality ultimately transforms the way network professionals work, unlocking efficiencies, enhancing security, and fostering a new level of trust in AI’s role in network operations.