Migrate your Yuma AI data
AI agent layer that installs inside Gorgias, Zendesk, and other helpdesks to autonomously resolve ecommerce support tickets at scale.
In its favor
Why people choose Yuma AI
The signal that keeps Yuma AI on the shortlist. Sourced from G2, Capterra, and customer scoping calls.
Ecommerce brands on Shopify, Gorgias, or Zendesk plug Yuma in without replacing their stack — no rip-and-replace, just an AI layer that reads existing ticket data and writes back autonomous replies.
Top deployments claim 80–89% full automation on WISMO, returns, refunds, and subscription change tickets, reducing agent backlogs without additional headcount.
Multichannel coverage across email, live chat, WhatsApp, Instagram, Facebook, TikTok Shop, SMS, and review threads in 180+ languages with a single configuration.
Guidelines feature lets merchants codify brand policies as rules the AI must follow, reducing hallucination risk compared to generic LLMs with no guardrails.
Built-in analytics dashboard surfaces resolution rates, CSAT scores, and automation health, giving CX managers visibility without a separate BI tool.
The per-resolution pricing model means a viral marketing campaign that spikes ticket volume also spikes the monthly bill — some teams find financial planning unpredictable and feel penalised for success.
Setup requires booking a demo, going through sales, and waiting for an account manager to configure Auto-Pilots — not a self-serve, plug-and-play experience for smaller teams wanting quick time-to-value.
AI hallucinations persist as the most cited complaint in G2 reviews; despite Yuma's 15–20 QC checks per reply, manual review overhead remains a friction point that some teams find unacceptable.
No voice or phone channel support limits utility for brands handling high volumes of inbound calls, pushing teams toward alternatives like Ringly.io that cover phone support.
As a thin layer on top of a helpdesk, Yuma adds cost on top of an existing platform subscription — for lean teams the combined spend is hard to justify versus a fully integrated AI-native helpdesk.
Reasons to switch
Why people leave Yuma AI
The recurring reasons buyers give for replacing Yuma AI. Presented as facts, not knocks.
Platform scorecard
Strengths, weaknesses, and where Yuma AI fits
Grades across six dimensions, plus a SWOT-style view of where the platform shines and where it falls short.
SWOT — strengths, weaknesses, and use-case fit
Strengths
Weaknesses
Where it works
Where it struggles
Pricing tiers
Yuma AI pricing overview
Yuma AI switched to a performance-based billing model where customers pay per fully autonomous ticket resolution. The standard tiers start at $350/month for 500 resolutions, $650/month for 1,000 resolutions, and $900/month for 1,500 resolutions, with enterprise custom pricing above that. Because billing is tied directly to resolution count rather than seat count or flat fee, costs scale with ticket volume — a successful viral campaign that drives more support requests also drives a higher monthly invoice.
Standard (500 resolutions)
Tier 1 of 4
$350/month
What's included
Need help selecting your Helpdesk?
Book a free 30 minute consultationPricing is informational. FlitStack AI does not bill on Yuma AI's schedule — see our quote-based pricing →
What gets migrated
Yuma AI object support
Object-by-object support for Yuma AI migrations. Per-pair details surface during scoping.
Tickets
Mapping requiredYuma reads Tickets from the host helpdesk (Gorgias, Zendesk, Kustomer) and writes AI-generated replies and resolution status back into the ticket thread. We preserve the full ticket body, metadata, and AI-authored content as a merged record. Destination AI platforms will need to interpret the embedded auto-reply blocks.
Customers
Fully supportedCustomer profiles live entirely in the host helpdesk. Yuma reads customer name, email, order history, and contact records to ground AI replies. We carry all customer fields through to the destination unchanged.
Companies/Accounts
Fully supportedCompany-level data (if the helpdesk uses it, e.g., Zendesk Organizations) is read-only from Yuma's perspective. No transformation is needed.
Agents
Mapping requiredYuma's Auto-Pilot agents are a separate logical layer, not a 1:1 map to human agents. We export Auto-Pilot agent configs as structured JSON and map escalation routing rules to the destination platform's equivalent agent or team assignment model.
Teams
Mapping requiredYuma routes edge-case tickets to specific human teams based on rules configured in Flows. We map these team assignments to the destination's team or queue structure, flagging any teams that exist only in Yuma's escalation config.
Custom Ticket Fields
Mapping requiredYuma respects and populates custom fields defined in the host helpdesk (e.g., order ID, return reason, subscription tier). We preserve all custom field values at migration time and map them to destination field names where naming conventions differ.
Conversations/Messages
Fully supportedEvery message in a ticket thread is preserved, including Yuma's auto-replies. We flag which messages were authored by a Yuma Auto-Pilot versus a human agent, so the destination can use this signal for retraining.
Attachments
Fully supportedInline attachments on tickets (images, PDFs, order screenshots) are carried over via the helpdesk API. Yuma does not store its own attachment blob — we pull from the host platform as normal.
Tags
Fully supportedYuma applies its own internal tags during processing (e.g., resolution type, automation status). We export all tags applied by Yuma alongside the ticket so the destination can use these for classification.
KB Articles
Not in this platformYuma does not own or host a knowledge base — it reads from your helpdesk's KB or Shopify product data at inference time. We migrate the KB articles from the host platform directly; Yuma's knowledge configuration is a read-access setting, not a standalone object.
Guidelines
Mapping requiredGuidelines are Yuma's branded-policy rules that constrain AI behaviour and prevent hallucinations. Exported as structured JSON (conditions, actions, allowed channels). Most destination platforms do not have an equivalent native concept — we document the full rule set for manual recreation or custom automation build-out.
Flows
Mapping requiredFlows are Yuma's visual workflow builder for automating ticket routing, triggers, and escalation sequences. We export Flow definitions as JSON and map trigger conditions to the destination platform's automation model where equivalents exist.
Integrations
Not in this platformYuma's direct integrations with Shopify, Recharge, and Klaviyo are outbound API connections that exist only within Yuma. These must be re-established in the new platform independently of the migration export.
| Object | Support | Notes |
|---|---|---|
| Tickets | Mapping required | Yuma reads Tickets from the host helpdesk (Gorgias, Zendesk, Kustomer) and writes AI-generated replies and resolution status back into the ticket thread. We preserve the full ticket body, metadata, and AI-authored content as a merged record. Destination AI platforms will need to interpret the embedded auto-reply blocks. |
| Customers | Fully supported | Customer profiles live entirely in the host helpdesk. Yuma reads customer name, email, order history, and contact records to ground AI replies. We carry all customer fields through to the destination unchanged. |
| Companies/Accounts | Fully supported | Company-level data (if the helpdesk uses it, e.g., Zendesk Organizations) is read-only from Yuma's perspective. No transformation is needed. |
| Agents | Mapping required | Yuma's Auto-Pilot agents are a separate logical layer, not a 1:1 map to human agents. We export Auto-Pilot agent configs as structured JSON and map escalation routing rules to the destination platform's equivalent agent or team assignment model. |
| Teams | Mapping required | Yuma routes edge-case tickets to specific human teams based on rules configured in Flows. We map these team assignments to the destination's team or queue structure, flagging any teams that exist only in Yuma's escalation config. |
| Custom Ticket Fields | Mapping required | Yuma respects and populates custom fields defined in the host helpdesk (e.g., order ID, return reason, subscription tier). We preserve all custom field values at migration time and map them to destination field names where naming conventions differ. |
| Conversations/Messages | Fully supported | Every message in a ticket thread is preserved, including Yuma's auto-replies. We flag which messages were authored by a Yuma Auto-Pilot versus a human agent, so the destination can use this signal for retraining. |
| Attachments | Fully supported | Inline attachments on tickets (images, PDFs, order screenshots) are carried over via the helpdesk API. Yuma does not store its own attachment blob — we pull from the host platform as normal. |
| Tags | Fully supported | Yuma applies its own internal tags during processing (e.g., resolution type, automation status). We export all tags applied by Yuma alongside the ticket so the destination can use these for classification. |
| KB Articles | Not in this platform | Yuma does not own or host a knowledge base — it reads from your helpdesk's KB or Shopify product data at inference time. We migrate the KB articles from the host platform directly; Yuma's knowledge configuration is a read-access setting, not a standalone object. |
| Guidelines | Mapping required | Guidelines are Yuma's branded-policy rules that constrain AI behaviour and prevent hallucinations. Exported as structured JSON (conditions, actions, allowed channels). Most destination platforms do not have an equivalent native concept — we document the full rule set for manual recreation or custom automation build-out. |
| Flows | Mapping required | Flows are Yuma's visual workflow builder for automating ticket routing, triggers, and escalation sequences. We export Flow definitions as JSON and map trigger conditions to the destination platform's automation model where equivalents exist. |
| Integrations | Not in this platform | Yuma's direct integrations with Shopify, Recharge, and Klaviyo are outbound API connections that exist only within Yuma. These must be re-established in the new platform independently of the migration export. |
Gotchas
What to watch for in Yuma AI migrations
Issues we've hit on past Yuma AI migrations, tagged by severity. FlitStack AI handles every one — surfacing them up front because buyer engineering teams want to know.
Per-resolution billing inflates costs during peak volume
Yuma owns no standalone data — migration is always helpdesk-centric
Guidelines and Flows require manual recreation at destination
No phone/voice channel creates a migration gap
| Severity | Issue |
|---|---|
| High | Per-resolution billing inflates costs during peak volume |
| High | Yuma owns no standalone data — migration is always helpdesk-centric |
| Medium | Guidelines and Flows require manual recreation at destination |
| Medium | No phone/voice channel creates a migration gap |
Leaving Yuma AI?
Where Yuma AI customers move next
7 destinations Yuma AI can migrate to.
How a Yuma AI migration works
Four steps, Yuma AI-specific
Connect
OAuth 2.0 via host helpdesk platform into Yuma AI. Scopes limited to read-only on the data we move.
Map
We translate Yuma AI-specific structures (custom fields, objects, value lists) to the destination's model.
Sample
Test with a 50–200 record subset to validate Yuma AI quirks before production.
Migrate
Full migration with Yuma AI rate-limit handling. Rollback available throughout.
FAQ
Yuma AI migration FAQ
Answers to the questions buyers ask most during Yuma AI migration scoping. Not seeing yours? Book a call.
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