Today's network environments are too complex to track by purely manual efforts. With digital twin technology, IT teams can build a virtual model of the production network and use it to validate configurations, simulate changes, and streamline management.

The use of digital twins – digital representations of physical objects or systems – is on the rise. Enterprises can use digital twins to replicate their IT environments, including infrastructure, network equipment, and Internet of Things (IoT) devices, and then run simulations to test the impact of changes and to optimize performance. They can be used to validate the current state of a network, for example, and test configuration changes, firmware updates, or adjustments to security policies.

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Natural language prompts put the power of NQE into the hands of every networking engineer

As featured in Network World, Forward Networks has raised the bar for network digital twin technology with AI Assist. This groundbreaking addition empowers NetOps, SecOps, and CloudOps professionals to harness the comprehensive insights of NQE through natural language prompts to quickly resolve complex network issues.

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AI Assist: Transforming Network Operations:

Recognizing the persistent challenges faced by engineers in accessing hybrid, multi-cloud network data amid vendor diversity and network complexity, Forward Networks introduced AI Assist, available today as part of release 24.1. The new feature facilitates Network Query Engine (NQE) searches using natural language prompts, allowing engineers of varying skill levels to conduct sophisticated network queries with a minimal learning curve. The feature also generates natural language explanations for queries, fostering improved collaboration and understanding within teams.

Building on the Industry’s Most Comprehensive Networking Data Library:

Leveraging its extensive NQE library, the capability will be continuously improved through use. A world-class networking large language model (LLM) combined with the industry’s most comprehensive network digital twin delivers the AI outcomes that users can trust.

Learn more about Forward Networks’ AI implementation at www.forwardnetworks.com/ai

With the combined challenges of tight IT budgets and scarcer technical talent, it’s becoming imperative for enterprise network pros to embrace automation of processes and the way infrastructure responds to changing network traffic.

Not only can automation help address these problems, they can also improve overall application-response time by anticipating and addressing looming congestion. Modern applications, such as virtual reality and artificial intelligence, and architectures that incorporate IoT and hybrid cloud have yet to reach their true potential because network capacity seems to always lag behind demand.

A common problem is that too much networking infrastructure is still manually maintained and managed, but major vendors are starting to addressing these issues, as are startups that seek to break bottlenecks through automation.

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