Why Spark Felt Different From Every Other AI Support Tool
Brandon Woods, Keysight Technologies, on the Difference Between a DEX-Powered IT Agent and a Generic AI Assistant
“Spark’s real power is the Nexthink data behind it. It can reason over the live environment, understand the remote actions we already use, and help find patterns that would take much longer to uncover manually.” — Brandon Woods, Keysight Technologies
AI has made its way into IT support, but for many employees, getting help still depends on how quickly support can understand what is happening on their device. When an issue happens, employees may still need to explain what they are seeing, wait while diagnostics are collected, and rely on support to piece together what changed before the issue can be resolved.
This is what made Nexthink Spark stand out to Brandon. Instead of acting like another generic AI assistant, Spark works from the live endpoint data, remote actions, and operational context already available in Nexthink. It gives employees a more informed support experience from the start, helping them resolve issues faster and get back to productive work sooner.
The challenge: AI without live operational context
Before Spark, Brandon’s team had to manually gather device context before AI tools could help. Even when those tools produced useful answers, support first had to collect the right information, export it, and feed it into something like Copilot. Every step added time, and the setup became harder to maintain as the environment evolved.
Most AI assistants could reason over the data they were handed, but they were not connected to the systems, telemetry, and operational context needed to support employees in real time. That gap left employees waiting.
The solution: An AI assistant built on live endpoint data
For Keysight, Spark’s value came from its native connection to the Nexthink ecosystem. Instead of asking employees to restate issues or waiting on manual context-gathering, Spark works from the live diagnostics, remote actions, and endpoint signals already in Nexthink.
Spark also understands and uses Nexthink remote actions directly. Brandon contrasted this with virtual agents like Moveworks, where teams must build and maintain a separate conversation workflow for every remote action. With Spark, a new remote action becomes available to the AI assistant with a single checkbox, and stays in sync as it evolves, with no parallel workflow to maintain.
That same connection improves how Spark supports employees in the moment. When employees in one office started seeing blue screens across multiple HP devices, Spark did not need anyone to describe the problem or assemble a history. It drew on the live endpoint context already in Nexthink, including surrounding device conditions, recent software changes, and available remediation actions, and surfaced the likely cause along with the actions to address it.
The result: a transformed IT support experience for employees
“It’s really good at finding needles in haystacks and correlating data and finding patterns that are hard to see.” — Brandon Woods, Keysight Technologies
Brandon expected Spark to feel like other AI assistants, but it did not. Because Spark was connected to live Nexthink data and approved remediation actions, employees could get more informed help without supplying every detail from scratch. That meant Spark could solve issues in the moment instead of just suggesting what to try next.
Takeaway
For Keysight, Spark made GenAI practical for IT support by embedding AI into the data, diagnostics, and approved actions needed to help employees resolve issues. It reduces support friction, accelerates issue resolution, and creates a more scalable path from reported symptom to trusted remediation.
For organizations looking to modernize support, Spark shows what becomes possible when every employee has a real-time personal IT agent at their fingertips.
