Neo Insights

Neo Insights analyzes your closed tickets and turns them into a projected return on investment from automation: how many hours and how much money you could reclaim, which work to automate first, and how to set it up. Open it from Insights in the dashboard. Your first report runs automatically once your PSA sync finishes. After that you can run new reports any time — for your whole desk, for a single end-client company, or for specific months — and switch between the reports you’ve already run without re-running anything.

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What’s in the report

The Categories view answers one question: what high-level categories do your tickets fall into, and what could automating each one save? Total annual savings opportunity — one line at the top, and the only headline figure: money per year and hours per year. It updates when you edit the minutes per ticket in the table. Savings by category — every category ranked by projected monthly savings. Open a row to see its sub-categories and the agents and tools that would automate it. Savings breakdown — a chart of where the projected savings come from, by category. Analysis details — the parameters behind the numbers:

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Switch between saved reports

Every report Neo runs is saved. The report switcher in the top-right of the Insights page shows which report you’re viewing (its company and time window) and lists every saved report — one per company-and-months combination, with the date it was run. Pick one to open it instantly; nothing is re-run and no analysis is consumed.

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Run a new analysis

Use New analysis in the top-right (next to the report switcher) to open the settings and run a fresh report.

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Choosing months

The month picker lists every month you have ticket history for, newest first, and you can select several at once — including non-consecutive months. Neo analyzes only the tickets from the months you pick and annualizes from what it observed. Choosing months that span a limited part of the year can skew seasonal categories, so the analysis period shown on the report always reflects the exact window that was used.

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When a company doesn’t have enough tickets

A meaningful analysis needs at least 30 closed, AI-summarized tickets. When you scope to a company that has fewer than that in your chosen window, Neo automatically widens the window to all time for that company and tries again — so smaller clients still get a report where the data allows. If there still aren’t enough tickets, Neo shows a clear “not enough data” message instead of an unreliable projection; pick a different company or period and try again.

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Problems

The Insights page has two views, switched with the tabs under the title. The line under the title names the question the open view answers. Categories is the report described above. Problems answers a different question: which types of tickets do your technicians still resolve by hand? It shows the specific, recurring problems, measured from your own ticket data. Neo draws a random sample of closed tickets from the chosen window, groups tickets that need the same fix, and reads how each group was resolved. Grouping happens in two passes. Tickets written almost the same way, such as an alert stream, group first. Neo then writes a list of the jobs your desk does from the remaining tickets and files each of those tickets under one job, so requests worded ten different ways still land in one row. A row that holds more than one runbook is split, at most eight ways, and a row with fewer than eight sampled tickets goes to the long tail. The sample is drawn in two parts, alerts and system mail on one side and tickets people raised on the other, so that a busy alert stream does not crowd out the problems your users bring you. Each part is scaled to its own share of your desk, so the counts stay true. Each row is one problem, such as INKY User Reported Spam Blocking or Exchange Online Mailbox Delegation, with: Open a row to see the steps technicians take today, including the different paths similar tickets follow, what still needs a person, any system an agent may need access to, and example tickets. A chip under each problem name says whether Neo can take the work on with what you have today:

• Ready with current tools (solid green) means every step has a route through an integration you have connected. The steps under Still needs a person still need a person.
• Ready · connect (green, dashed border) means every step has a Neo route, and one or more of the integrations it uses is not connected yet, such as your RMM or IT Glue. Open the row to see the full list under Connect in Neo: each name there opens that integration on the Integrations page, and the RMM and PSA open the page itself, where you pick your vendor.
• May need (amber) names a system no Neo integration reaches, such as Google Workspace or Duo. A system that Neo could reach only through a Custom API you would build yourself counts here too, and so does an order for hardware through a cloud marketplace, whose Neo integration reads licence subscriptions and changes seat counts only.

Problem maps built before this check existed show no Ready chip, and maps built before the links existed show the names under Connect in Neo without links; build a new map to get both. Neo’s share has two readings, printed as resolved · touched. Resolved means the ticket closed assigned to Neo. Touched means a Neo agent ran on the ticket, whoever closed it, so a triage or chase agent counts here and not under resolved. Both are split by close date into the last 30 days of the window and the months before them, so a problem you put Neo on last month shows the change at once. A small ▲ or ▼ after a value says that share moved from before the last 30 days to inside them; a move under 3 points shows no mark. Hover a value to read the two last-30-day shares in words. A row with fewer than 10 sampled tickets in the last 30 days shows its whole-window shares instead, and the hover says so. The Last 30 days tile carries the same two readings for the whole desk, and hovering it shows a small chart of both by month when the map’s tickets closed in more than one month. Problem maps built before these readings existed show the whole-window resolved share alone. Hours come from your PSA time entries. Median time counts only the tickets that carry one. Opportunity also counts the tickets without one: each of those adds the median logged time of its problem, or the median of the whole desk when the problem has 1 to 4 logged tickets, and the row says desk median when that happened. A problem that no technician has logged time on gets no estimate and shows no time logged, because a stream nobody logs time on is most often closed by a tool. Such a row ranks by ticket volume alone. Neo uses the median because on a desk that logs a small share of its tickets, the logged ones tend to be the long ones. The note under the table says what share of tickets carry a time entry; the lower that share, the more of the opportunity is estimate. Problem maps built before this estimate existed show the logged hours alone. Neo never builds a problem map on its own. Press Build problem map for the first one, or New problem map to run one for a company or a set of months, the same scoping as the category report. To leave a few companies out of a whole-desk map, such as an internal company or a client that has left, pick them under Exclude companies; the map’s header and its entry in the report switcher name what was left out. Expect a run to take about 10 to 20 minutes, an estimate from our test desks that depends on ticket volume, and saves alongside your other problem maps in the report switcher.

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Good to know

• Who can run it — only tenant admins can start a new analysis or problem map. Everyone with access can view saved reports.
• Re-running is safe and cheap — each run replaces the saved report for that exact scope; running a company or month view never overwrites your whole-desk report.
• Export — use Export PDF to share the current report outside the dashboard.

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Related

• Analytics — measure live workflow performance and credit consumption once your automations are running.
• Company mapping — how Neo recognizes the same end-client company across your connected systems, which is what powers the company filter here.