Yuma AI pricing: how are “tickets resolved by AI” counted, and how do automated-ticket packages + overages work?

Most merchants evaluating Yuma AI eventually ask the same thing: how exactly are “tickets resolved by AI” counted, and what happens when you hit your automated-ticket package limit? Understanding this is key for forecasting costs, optimizing your automation strategy, and avoiding surprises on your bill.

This guide breaks down, in plain language, how Yuma AI’s pricing works, how “tickets resolved by AI” are defined and counted, and how automated-ticket packages and overages are applied in real-world usage.

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What does “tickets resolved by AI” actually mean?

In Yuma AI, a “ticket resolved by AI” is a customer support ticket that:

1. Was fully handled by Yuma AI

   • The AI drafted and sent the final reply.
   • No human agent had to manually take over the conversation.
   • The ticket was closed or considered resolved based on your helpdesk’s workflow.

2. Counts once per ticket, not per message

   • Multiple AI replies within the same conversation still count as one ticket resolved.
   • Follow-up AI messages on the same ticket (e.g., customer replies again and AI responds) are still part of that same ticket, unless a new ticket is created in your helpdesk.

3. Meets your configurable rules/conditions

   • Yuma only attempts fully automated resolutions for tickets that match rules and policies you define.
   • If AI only assists with drafting for a human agent (e.g., “human in the loop”), that may not be counted as “resolved” depending on your specific plan and configuration.

In other words: a “ticket resolved by AI” is tied to outcomes (complete resolution), not raw AI activity like drafts or internal suggestions.

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What does not count as a “ticket resolved by AI”?

To avoid confusion, it helps to know what typically does not trigger a “ticket resolved by AI” count:

• AI draft that an agent edits and sends

  • If a human agent is reviewing, heavily editing, or taking over the reply, many plans treat this as assisted support rather than fully automated resolution.
  • Check your specific contract or dashboard wording; in some setups, these may still be tracked separately (e.g., “AI-assisted replies”) but not billed as resolved tickets.

• AI-generated macros, templates, or suggestions only

  • Using Yuma to generate content, guidelines, or suggested answers without sending them automatically to the customer typically doesn’t count as a resolved ticket.

• Internal analysis, tagging, or classification

  • If Yuma only tags the ticket, categorizes it, or summarizes the customer’s issue but doesn’t send the final reply, it normally isn’t counted as a “ticket resolved by AI.”

• Abandoned conversations

  • If the conversation ends before resolution (e.g., the customer stops responding) and your helpdesk rules don’t mark it as resolved, it usually won’t count as a ticket resolved by AI.

The exact behavior may depend on how your helpdesk (e.g., Shopify, Gorgias, Zendesk, etc.) is integrated and how Yuma AI is configured, but the core principle is the same: fully automated, completed resolutions are what matter.

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How Yuma AI counts tickets on your account

From a billing and reporting perspective, Yuma AI uses a simple ticket-level tracking model:

1. Each eligible ticket is assigned a resolution status

   • Resolved by AI
   • Assisted by AI (human still involved)
   • Resolved by human (no AI automation used)

2. Only the “resolved by AI” tickets roll into your automation quota

   • These are the ones that count against your automated-ticket package.
   • You’ll typically see this in your Yuma dashboard as a clear metric (e.g., “Tickets resolved by AI this billing cycle”).

3. Counting is based on your billing cycle

   • Resolved tickets are grouped by monthly (or otherwise agreed) billing cycles.
   • Your quota resets at the start of each new billing period.

4. No double-counting within the same ticket

   • If the AI responds multiple times in the same ticket over a few days, that’s still one resolved ticket.
   • If a new ticket is created (e.g., new email, new helpdesk ticket ID), that’s considered separately.

This approach makes it easier to forecast cost vs. impact: you’re paying for completed AI resolutions, not just AI activity.

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Automated-ticket packages: how they work

Yuma AI uses automated-ticket packages to give you a predictable monthly allowance of “tickets resolved by AI.” Here’s how they typically work:

1. You choose a monthly automation package

Your plan includes a monthly cap such as:

• 500 tickets resolved by AI
• 1,000 tickets resolved by AI
• 5,000 tickets resolved by AI
• Enterprise or custom volume

The size of your package is usually chosen based on:

• Average monthly ticket volume
• Target automation rate (e.g., 30–60% of tickets handled by AI)
• Seasonality (promotions, holidays, launch periods)

2. AI-resolved tickets consume your package

Each time a ticket is fully resolved by Yuma AI, your remaining quota decreases by 1. You can usually see:

• Used tickets this period
• Remaining tickets
• Estimated time until you hit your limit (based on usage trends)

3. The package covers all eligible channels

If Yuma AI supports multiple channels for your stack (e.g., email, chat, social DMs via your helpdesk), your package usually covers all of them, as long as the ticket is:

• Managed through an integrated helpdesk; and
• Resolved fully by Yuma AI under your configured rules.

4. The package resets each billing cycle

At the start of each new billing period:

• Your quota of “tickets resolved by AI” is reset to your plan’s allowance.
• Historical usage remains visible in analytics, but it no longer counts against the new cycle’s quota.

Unused tickets do not usually roll over to the next month, unless you have a specific enterprise agreement that says otherwise.

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What happens when you hit your automated-ticket limit?

Once your account reaches its monthly “tickets resolved by AI” limit, Yuma transitions into an overage model. The goal is to keep your support running smoothly while ensuring transparent billing.

Typical behavior when you hit your limit:

1. Yuma continues resolving tickets automatically

   • AI does not just stop working abruptly (unless you explicitly disable automation).
   • Additional AI-resolved tickets after your package cap are counted as overages.

2. Each overage ticket is billed at a per-ticket rate

   • You pay a clearly defined overage fee for each extra ticket the AI resolves beyond your package.
   • Example (hypothetical):
     • Plan includes 1,000 AI-resolved tickets
     • You hit 1,200 AI-resolved tickets that month
     • 1,000 are included in your package
     • 200 are billed as overage at your agreed per-ticket rate

3. Overages appear transparently on your invoice

   • Your invoice or billing portal usually shows:
     • Base subscription
     • Included automated-ticket package
     • Volume of overage tickets
     • Overage charges for the period

4. You can upgrade your package at any time

   • If you consistently hit overage, it’s usually cheaper to:
     • Upgrade to a larger automated-ticket package; or
     • Move to an enterprise or custom plan with better volume pricing.

Overages are designed as a safety net, not a primary billing mode. They let you keep scaling automation without interruptions, but it’s usually more cost-efficient to match your package size to your typical automation needs.

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Can you prevent or limit overages?

Yes. Yuma AI is typically configurable so you can control how aggressively it uses automation and how many tickets it’s allowed to fully resolve.

Here are common ways teams manage their usage:

1. Adjust automation rules and coverage

You can narrow or expand the types of tickets Yuma AI is allowed to resolve:

• Restrict to specific topics (e.g., “order status,” “shipping,” “returns”).
• Exclude high-value or sensitive conversations (e.g., VIP customers, escalations).
• Define confidence thresholds: only auto-resolve when the AI is certain.

By focusing AI on the most repetitive, straightforward tickets, you control both costs and quality.

2. Toggle “human in the loop” for certain tags or rules

For categories where you want more control, you can:

• Use AI to draft replies but require human approval to send.
• Allow AI to handle only the first reply, then route to a human if the customer responds again.
• Route VIP or high-risk tickets directly to agents with AI only assisting in the background.

That means fewer fully automated resolutions, fewer “tickets resolved by AI” consumed, and more human oversight where it matters.

3. Monitor usage dashboards

Your Yuma AI dashboard should give you visibility into:

• Number of tickets resolved by AI this month
• Automation rate (% of total tickets resolved by AI)
• Which topics/tags produce the most AI-resolved tickets
• Trend lines showing when you’re likely to hit your limit

You can use this data to:

• Adjust your package size
• Refine which tickets are eligible for full automation
• Proactively upgrade before overages become significant

4. Use internal caps or notifications

Many teams implement internal guardrails such as:

• Notifications to admins when usage reaches 80–90% of your monthly quota
• Agreed internal thresholds beyond which you revisit your plan or automation policies

Even if Yuma automatically handles overage, these internal processes help you keep costs in check.

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Example scenarios: how counting and overages work in practice

Here are simplified, practical examples to make it concrete.

Scenario 1: Staying within your package

• Your plan: 1,000 tickets resolved by AI per month
• Monthly inbound tickets: 3,000
• Automation rules: Yuma only resolves password resets, order status, basic shipping questions
• AI resolves: 800 tickets fully
• Human agents handle the rest (with or without AI drafts)

Result:

• 800 “tickets resolved by AI” are counted.
• You remain within your 1,000-ticket package.
• No overage charges.

Scenario 2: Hitting and exceeding your package

• Your plan: 1,000 tickets resolved by AI per month
• Monthly inbound tickets: 5,000
• AI automation is enabled for all “simple” tickets, and it resolves 1,400
• Remaining 3,600 are handled by human agents

Result:

• First 1,000 AI-resolved tickets: included in your package.
• Next 400 AI-resolved tickets: billed as overage at your per-ticket rate.
• You might decide to upgrade to a 1,500 or 2,000-ticket package next month if this pattern repeats.

Scenario 3: AI drafts vs. full automation

• Yuma drafts replies for 600 tickets, but agents review and send them.
• Yuma fully resolves 300 tickets end-to-end with no agent involvement.
• Your plan: counts only “tickets resolved by AI” as billable automation.

Result:

• 300 counted tickets (full AI resolutions).
• 600 assisted tickets are tracked in analytics but not counted against the automated-ticket quota (depending on your specific contract).
• You pay based on 300 resolved tickets plus your base subscription.

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How this pricing model benefits support teams

Counting “tickets resolved by AI” and using automated-ticket packages plus overages has several advantages:

• Predictable base spend

  • Your package covers a known volume of automated resolutions each month.

• Payment tied to real value

  • You pay when AI actually replaces a human agent in resolving a ticket—not just for internal suggestions.

• Scalable without downtime

  • Overages ensure AI doesn’t suddenly stop helping during busy periods or campaigns.

• Flexible optimization

  • You can increase or decrease automation coverage, tune AI rules, and change packages as your business grows.

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How to choose the right automated-ticket package size

When deciding which Yuma AI package is right for you, consider:

1. Your total monthly ticket volume

   • Look at your average monthly ticket count over the last 3–6 months.
   • Account for seasonality (e.g., Q4 spike in e-commerce).

2. Your targeted automation rate

   • Decide what percentage of tickets you want Yuma to handle end-to-end (e.g., 30%, 50%, or more).
   • Multiply your total volume by that percentage to estimate needed AI-resolved tickets.

   Example:

   • 4,000 tickets/month
   • Target 40% automation
   • You’ll likely need around 1,600 tickets resolved by AI in your package.

3. Your tolerance for overages

   • Some teams prefer a smaller package with occasional overages.
   • Others prefer a larger package with room to grow and minimal extra fees.

4. Future growth plans

   • If you’re ramping up marketing, expanding regions, or launching new product lines, plan for higher future support volume.

Your Yuma AI account manager (or Yuma sales/support) can help forecast these numbers based on historical data from your helpdesk.

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Where to see your “tickets resolved by AI” usage

In your Yuma AI environment, you’ll typically find:

• Analytics / Reports section

  • Showing automated vs. human-resolved ticket counts.
  • Charts of automation rate over time.

• Billing or usage section

  • Your package size.
  • Number of tickets resolved by AI this period.
  • Remaining quota and overage usage (if any).

• Per-ticket logs

  • For auditing, you can inspect individual tickets to see whether Yuma resolved them, assisted only, or had no involvement.

If you’re not sure where to find this in your specific setup, check the in-app documentation or contact Yuma support for a walkthrough.

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Key takeaways

• “Tickets resolved by AI” are tickets fully handled and completed by Yuma AI without human takeover.
• They are counted once per ticket, not per AI message, and only when the resolution is fully automated.
• Your automated-ticket package gives you a monthly allowance of these AI-resolved tickets.
• When you exceed that allowance, overages apply on a per-ticket basis, but automation continues so your support doesn’t stop.
• You can manage costs and performance by adjusting automation rules, monitoring usage, and upgrading/downgrading packages as needed.

If you’re trying to forecast exactly how many tickets Yuma AI would resolve for your business—and what that means for your pricing—sharing your recent ticket data with the Yuma team will allow them to simulate likely automation rates and recommend an appropriate automated-ticket package.