Remote Built a World-Class IT Help Desk with Orchestrated Notion Custom Agents

With search improving, James focused on the next bottleneck. IT requests often aren’t just questions, but require action, triage, and follow-through. Remote needed a system that could handle the end-to-end lifecycle of support work while keeping employees in the flow.

James’s solution is an orchestrated system of Custom Agents that replaces a more complex, linear and entirely human managed setup. The goal wasn’t to build a “Superagent,” but a team of specialized agents with clear roles and tight controls—because a single agent trying to do everything quickly becomes too complex and unpredictable.

In the current workflow, the experience starts in Slack, where Remote employees already spend their days. Requests come in through a lightweight intake interaction like an emoji reaction, capturing plain-language context and the right metadata up front. From there, the agent system takes over.

What happens next looks less like a bot answering questions and more like an IT team running a playbook—only the roles are automated.

1. Intake and creating tickets. This Slack-triggered intake agent captures the issue in plain text and creates a ticket in Notion, enriched with structured fields like priority, team/department, and a link back to the original thread. When necessary, the agent can also pull core user context via a read-only Worker integration for Okta to improve routing and reporting.

2. Triage. Another agent acts like the front line: it checks whether the request belongs with IT or should be redirected to another team, then searches across the knowledge base, historic tickets, Slack context, and the web (when needed) to propose a diagnosis and next steps. In Remote’s setup, this process includes explicit confidence: the agent rates how sure it is, and can auto-approve certain decisions above a threshold—keeping humans in the loop where it matters most.

3. Device-specific help. When triage suspects a device problem, a specialized device-helper agent can pull details like the model, OS version, and last reboot time from Kandji, then return targeted guidance to the same Slack thread.

4. Follow-up and closure. Support isn’t just diagnosis, so a nudges agent runs daily, checking for tickets with no activity in 72 hours, prompting the requester, and auto-closing after repeated nudges—saving hours of manual “just checking in” work each week.

“We never taught it that—it’s not in the knowledge base.” James hears versions of that reaction often. Remote’s IT knowledge base remains the source of truth in Notion, but its agents now keep a private working journal alongside it—capturing new patterns, using repeated outcomes to improve triage, and moving the most useful fixes back into the main knowledge base. It’s the kind of self-improvement loop that James says “sparks joy when the agent saves us time later by self-solving a ticket.”

Throughout these interactions, the agent system is intentionally “human” in tone. James found that overly prescriptive instructions weren’t the answer; giving agents the freedom to “vibe” produced clearer, more helpful responses—and sometimes delightful ones, as when an agent congratulated someone on a promotion while still solving their problem.

At Remote, humans set the bar for AI, defining escalation paths, maintaining the knowledge base, refining instructions, and designing the guardrails that make automation trustworthy. What’s left over is execution: routing, retrieval, first-pass resolution, and consistent follow-through.

While 1 in 4 IT requests are fully resolved by agents from end-to-end, the rest are still supported by AI—for example, through ticket triage. This means the team can step in once the admin work is done and quickly carry the request over the finish line.

That human ownership shows up in how the system is built and maintained. James used AI to help write and refine instructions, but tested carefully—iterating in controlled environments with real ticket text and tuning for the right balance of structure and flexibility. The result is a support experience that’s faster for employees and more sustainable for IT.

Remote has seen a growing share of tickets resolved with significant agent involvement—whether that’s full resolutions or workflows that still require explicit human input. And because the system runs in Notion, Remote can keep improving it: updating instructions, refining routing, and enriching tickets with additional context.

Over the first few months, AI resolutions grew ~35% while overall ticket volume stayed flat, meaning AI is genuinely taking more work off the team's plate. Plus, the AI is getting more efficient by iterating on its own instructions, consuming 35% fewer credits and 7% less spend compared to its initial launch month.

Looking ahead, Remote is already experimenting with Workers that pull read-only context from other systems like Okta. The long-term direction is clear: carefully expand what automated systems can do while keeping humans in control of the outcomes and the standards.

Remote already ran its knowledge, processes, and team in Notion—so as IT requests scaled, they built an agent-powered help desk right where employees work. It keeps every request tied to the right context and moves tickets from intake to triage to follow‑up, bringing humans in only when needed.