On October 7, we returned to Networking Field Day (NFD) to introduce the next generation of NetBeez. We’ve been presenting at NFD for more than a decade now, our first appearance being in 2015. What is special about this time is the fact we covered what I think is the most significant evolution of the product since we started the company.
This was not just an opportunity to show how the idea behind NetBeez has evolved. That is, continuously measuring network performance from the user’s perspective, then helping teams use that evidence to decide what deserves attention, investigate problems, and verify improvements.
Our presentation covered that evolution in three parts: the vision behind NextGen, a hands-on look at network and Wi-Fi investigations, and AI-assisted workflows.
Here is a recap of what we covered.
From troubleshooting to continuous network-experience assurance
I opened the presentation with a problem familiar to many network teams: infrastructure dashboards can look healthy while users struggle with poor calls, slow applications, or unreliable connectivity.
NetBeez has always approached this gap through distributed agents that continuously test from where users connect. Those observation points now span offices, Wi-Fi networks, remote workers, data centers, and cloud environments.
With NextGen, we are building on those measurements to support a broader operational workflow:
- Detect what needs attention.
- Isolate the likely fault domain.
- Take action.
- Prove that the experience improved.
That workflow matters during an incident, but it also supports the work between incidents: investigating recurring degradation, reviewing conditions across locations, and validating network changes.
Following the evidence through Wi-Fi and VPN problems
Panos followed with a demonstration of how operators can move from an indication of degraded experience into the measurements behind it.
The first scenario involved a Wi-Fi sensor whose nearby access point became unavailable. The sensor connected to a more distant access point, preserving connectivity while experiencing weaker signal and degraded performance.
The investigation connected the access-point change with the change in wireless conditions and test results. A Wi-Fi scan helped establish that the preferred access point was no longer broadcasting.
The second scenario examined remote users experiencing degradation over a shared VPN path. Comparing the affected users and their measurements helped narrow the investigation toward a common dependency.
Both scenarios illustrated the same principle: continuous measurements become more useful when teams can examine their relationships and timing.
Bringing AI into the investigation
Panickos then demonstrated how operators can use natural language to work with NetBeez evidence.
The examples included investigating degraded experience, running ad hoc tests, and creating a monitoring target. We also covered MCP, which allows external AI tools to work with NetBeez data and capabilities.
The operational goal is to make investigations and monitoring tasks easier to perform while keeping the underlying evidence accessible.
An explanation should help an operator understand what happened, what supports that conclusion, and what to check next.
Closing the loop after a change
One theme connected all three sessions: an investigation should lead to a measurable outcome.
Once a team addresses a suspected problem, continuous testing provides a way to check whether performance recovered and whether that improvement holds.
That is central to our direction with NextGen. We want to help teams move through the complete process, from recognizing degraded experience to demonstrating that their action helped.
Watch the demonstrations
The full NetBeez presentation at Networking Field Day 41 is available on demand, with separate recordings for each session.
If you would like to explore how these workflows apply to your own network, offices, and remote users, request a NetBeez NextGen demo.
