Zendesk App
ResolveAI for Zendesk
ResolveAI for Zendesk reviews incoming tickets, applies policy-aware automation, enforces refund thresholds, and escalates edge cases before your queue backs up.
This Zendesk landing page now leads with how the product actually behaves: read the ticket, check the right context, resolve what fits your rules, and keep a visible audit trail when a human should step in.
Policy-aware. Refund thresholds enforced. Edge cases escalated.
- Designed around Zendesk triggers, webhooks, and agent-side visibility.
- Uses ticket history, requester context, and help-center content in the response flow.
- Shows confidence, policy checks, and outcome context in the sidebar instead of hiding the reasoning trail.
ROI Calculator
See what automated ticket resolution can save
Example: a team with 500 tickets/month can save about $2.5k/month at 35% automation.
Use one of the presets to start, then adjust the assumptions for your queue.
Estimated Monthly Impact
175
Automated tickets
$2,625
Monthly labor cost avoided
$85.75
Estimated ResolveAI cost
$2,539.25
Estimated net savings
Pricing uses a Starter-plan assumption of $0.49 per automated resolution.
What It Does
Built for the way Zendesk teams already work
The product pitch is simple: read the ticket, look up the right context, respond when the answer is clear, and surface the rest to the human queue with more structure.
Ticket-aware response flow
ResolveAI can inspect ticket details and prior comments before drafting a reply, so it behaves more like a support operator than a generic text generator.
Help-center search
Support content in Zendesk Help Center can be pulled into the response flow, which keeps answers aligned with the team's own published guidance.
Sidebar transparency
Agents can see confidence, tools used, and the outcome context inside the Zendesk UI instead of guessing what the AI actually did.
Demo Clarity
What a marketplace evaluator should understand quickly
The Zendesk page should answer four things fast: where the app sits, how it responds, how agents review it, and what happens when the app should not act alone.
A new ticket triggers the workflow
The app can start from a Zendesk trigger and send the ticket payload through the ResolveAI backend for analysis.
ResolveAI checks context before replying
It can look up ticket history, requester details, and help-center content before deciding whether a customer-ready answer is available.
Agents still see the reasoning trail
The sidebar app is there so a human can review confidence, tools used, and outcome context rather than treating the workflow as a black box.
Keep the proof story focused on what buyers care about: which policy was applied, whether the refund stayed under threshold, and why the action was allowed.
The sidebar should show confidence, action taken, and escalation logic so a support lead can understand the decision without digging through backend logs.
Low-confidence, high-value, or out-of-policy tickets should be routed back to the queue with context instead of pretending every ticket should auto-resolve.
FAQ
Direct answers for Zendesk teams
What does ResolveAI for Zendesk do?
It helps support teams respond to common Zendesk tickets faster by combining ticket context, help-center search, and agent-visible escalation paths.
Does it work entirely inside Zendesk?
The workflow is built around Zendesk triggers, ticket data, and a sidebar app, so the support team sees the automation in the system they already use.
Can agents review what the AI did?
Yes. The sidebar app is meant to expose confidence and tool usage so a human does not have to trust an invisible workflow.
When should a ticket still go to a human?
Cases that are ambiguous, risky, or low confidence should be escalated rather than auto-resolved, which keeps human judgment in the loop where it matters.
Next Step
Show the workflow, then let buyers install with confidence
This page should make the Zendesk value proposition obvious fast: what gets resolved automatically, which guardrails stay enforced, and where a human still steps in.