Rezolve DeskIQ reads twelve months of your own tickets and ranks what to automate first, with the projected hours behind each one. It can do that because Support Effectiveness measures every request end to end — including the ones that never became tickets.
90% → 10% after-hours IT dependency Black Angus Steakhouse
DeskIQ clusters twelve months of your IT tickets into real intent families — password resets, access requests, VPN, onboarding — and scores each on how much of it a machine can actually finish. Then it writes the flows, APIs and remediation straight into Creator Studio.
Illustrative DeskIQ output — your roadmap is generated from your own ticket history, not a guess you defend in a planning meeting. Click any opportunity to see the analysis behind it.
Most reporting starts at the ticket. This starts a step earlier — at every request that entered support, however it arrived — and follows each one to where it actually ended. In this sample month 1,065 requests came in and 613 became tickets. The other 452 are the ones ordinary reporting never sees, and the ones DeskIQ learns the most from.
Every request that entered support, however it arrived, followed to where it actually ended.
In · 1,065 requests · last 30 days
452never became a ticket42% of everything that came in
613became tickets58%
| From | To | Requests |
|---|---|---|
| Conversations started | Bot conversations | 470 |
| Conversations started | Direct live chat requests | 85 |
| Conversations started | Direct ticket requests | 65 |
| Bot conversations | Resolved using Knowledge | 180 |
| Bot conversations | Resolved via Automations | 140 |
| Bot conversations | Total live chats | 90 |
| Bot conversations | Total tickets | 60 |
| Direct live chat requests | Total live chats | 85 |
| Direct ticket requests | Total tickets | 65 |
| Total live chats | Resolved in live chat | 132 |
| Total live chats | Total tickets | 43 |
| Tickets from Portal | Total tickets | 210 |
| Tickets from Smart Mailbox | Total tickets | 140 |
| Tickets from Voice IQ | Total tickets | 95 |
| Total tickets | Tickets resolved | 498 |
| Total tickets | In progress | 115 |
A bot that deflects more by answering worse still draws a rising line. So satisfaction sits on the same weeks as deflection — if the two ever diverge you find out here, not in a QBR.
Closing quicker is only a win if the person on the other end agrees. Speed and satisfaction are plotted over the same weeks, so a queue being cleared rather than solved shows up as a split.
Rebuilt here from the shipped dashboard, with sample tenant data. Every figure on your own dashboard is drawn from your own tenant.
A knowledge author, an automation builder, a ticket agent and a chat agent do not need the same numbers. Each gets the cards that belong to their work.
Every dashboard has a sidekick built in. Type what you want to see in plain language and it builds the view: incidents by severity, SLA risk, automation trends. No report builder, no analytics queue, no waiting a sprint for a number you needed this morning.
A faithful, clickable recreation of the conversational dashboard: ask in plain language, get the answer and the chart.
Every figure below is from a named customer on the public record. Where a team hasn’t published a number, we don’t invent one for them.
“Rezolve.ai helped us reduce after hour calls to IT from 90% to 10%.”
Constance Mayaki, Programming ManagerAcross deployments, ticket deflection and autonomous resolution run 60–80% for common ticket types. Rated 4.8/5 on G2 (High Performer, Spring 2025) and 4.8/5 on Microsoft AppSource.
See what our customers say about us.
“Our vision was to modernize employee support with automation and AI — Rezolve.ai made that vision real.”
Rezolve.ai’s service desk intelligence clusters twelve months of your tickets into intent families, such as password resets, access requests, VPN and onboarding. It scores each one on how much of it a machine can actually finish, then ranks the opportunities by impact, with the projected hours behind each one.
Yes. The ranked opportunities feed straight into Rezolve Creator Studio, which drafts the workflows and automations so the recommendation becomes something that runs. Bring twelve months of ticket history to a demo and you leave with your top five opportunities ranked on your own queue.
Support Effectiveness follows every request from first touch to outcome, however it arrived: chat, portal, smart mailbox or voice. Most reporting starts at the ticket, so it misses requests resolved by knowledge, automations or live chat. Counting those shows true deflection, agent hours returned and SLA compliance in one view.
Rising deflection is not automatically good, because a bot that answers worse can still deflect more. Rezolve.ai plots satisfaction on the same weeks as deflection, and resolution speed on the same weeks as satisfaction. A queue being cleared rather than solved shows up as a split between the lines. Dashboards are also scoped by role, so each person sees the numbers for their own work.
Conversational dashboards let you ask your service desk a question in plain language and get the chart back: open tickets by priority, incidents by severity, SLA risk or automation trends. There is no report builder and no waiting on an analytics queue for a number you need today.
Trusted from JLL’s ~100,000-employee Ask Ethics rollout to TotalEnergies Denmark, Gesa Credit Union and Black Angus Steakhouse, and rated 4.8/5 on G2. See the same platform run your own IT, HR or Finance scenarios end-to-end: autonomous, governed, and fully explainable.
Bring twelve months of ticket history to the demo. DeskIQ ranks your top five automation opportunities on your own queue, with the projected hours next to each — you leave with the roadmap, not a slide about one.
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