Written by the team behind one of the largest Nexthink deployments in the world. This resource covers the platform from architecture to implementation: what it does, how it works, and how to get the most from it.
Last reviewed November 2026
Our Perspective
Most organizations that deploy Nexthink underutilize it. The platform collects extraordinary amounts of data (device telemetry, application performance, network quality, employee sentiment) and exposes it through a powerful analytics engine, a library of pre-built automations, and an AI layer that is maturing rapidly. Organizations that treat it as a monitoring dashboard get a fraction of the value available to organizations that build it into their DEX operating model. This guide is about the difference.
In This Guide
The guide is organized so that someone new to Nexthink can read from top to bottom, and an experienced admin can jump to the topic they need. Start with Architecture if you're new: everything else makes more sense once you understand how data flows through the platform.
How Nexthink Infinity is built: the Collector agent, data pipeline, cloud platform, AI layer, and integration ecosystem. With a detailed architecture diagram. Start here if you're new to the platform.
Nexthink's three AI agents: Spark (employee personal IT agent), Workspace (IT AI cockpit for investigations and insights), and AI Activation Hub, powered by AI Drive (AI tool usage observation and governance). How each works and what you need in place first.
Nexthink's employee communication and feedback product. Targeted Campaigns push surveys and notifications directly to employees' desktops: capturing sentiment data that no ticket system can provide.
Low-code workflow orchestration for IT operations. Build automated remediations, self-healing sequences, and on-demand diagnostics that Spark executes autonomously: no script expertise required.
How to build dashboards that drive decisions rather than decorate walls. Structuring for executive audiences vs. IT ops teams, the metrics that matter, and NQL-backed live widgets.
The strategic DEX view for IT leaders: the DEX score, benchmarking, organization filters, and what changed when Workspace became the default landing page in 2026.8.
How web and SaaS applications actually perform for employees: page loads, transactions, reliability, usage, synthetic monitoring, and AHEAD dashboards for application owners.
Nexthink Amplify embeds live device telemetry and one-click remediation inside your ITSM tool: giving service desk agents the context to close tickets faster and escalate less.
Nexthink Query Language: a plain-English guide for IT practitioners. Syntax fundamentals, common investigation patterns, and worked examples for the queries you'll actually need.
Practical Nexthink deployments: Microsoft 365 experience monitoring, VDI performance, security and compliance posture, software license reclamation, and employee onboarding automation.
Why This Matters
Nexthink has always collected an enormous volume of data. Before AI, that volume was as much a challenge as an asset: too much to analyze manually, too granular for human review at scale. The result was organizations drowning in telemetry they couldn't act on.
The introduction of Spark, Workspace, and AI Drive changes that equation fundamentally. AI agents can correlate signals across a hundred thousand endpoints simultaneously, surface anomalies no analyst would catch, and trigger remediation before the user ever opens a ticket. The tidal wave of data becomes an asset instead of a liability.
Nexthink's CEO has called 2026 the year of AI agent maturity. The organizations that have their DEX data infrastructure in place and a team that knows how to direct it will be the ones that capture that value.
Nexthink has also formalized its applied AI research in DEX Frontier Labs, a team working at the intersection of large language models, multi-agent systems, and enterprise IT at scale. It is a useful place to watch for where Spark, Workspace, and AI Activation Hub are heading next.