Comparison
ResolveKit vs Zendesk AI
Zendesk AI extends their traditional ticketing platform with automation. ResolveKit takes a fundamentally different approach — embedding resolution directly inside your product so issues never become tickets in the first place.
| Feature | Zendesk AI | ResolveKit |
|---|---|---|
| Architecture | Helpdesk / ticketing platform with AI add-on | Native embedded SDK (iOS + Android) |
| Where resolution happens | In the helpdesk — users leave your product | Inside your app — before a ticket is ever created |
| Product context | Help center articles and ticket history only | Deep — SDK has access to app state, screen, version, workflows |
| Can take action | Limited — auto-reply, classify, route tickets | Yes — executes product actions with approval guardrails |
| Approval system | No built-in approvals for AI actions | Policy-based approvals, user consent, operator control |
| Session traces | Ticket and conversation history | Full traces: context, proposals, approvals, outcomes |
| Open source | No — proprietary platform | Yes — MIT SDKs, AGPL backend, fully auditable |
| Self-host option | No | Yes — run on your own infrastructure, bring your own LLM keys |
| Mobile support | Mobile web help center | Native iOS (SwiftUI + UIKit) + Android (Compose + Views) |
| LLM flexibility | Fixed — Zendesk's own AI models | Any LLM via LiteLLM — OpenAI, Claude, Gemini, local models |
| Data residency | Zendesk-controlled regions | Your infrastructure — full data control |
| Compliance | SOC 2, GDPR (vendor-managed) | You control compliance via self-hosting |
| Analytics & insights | Built-in dashboards | Full session traces exportable for custom analytics |
| Pricing model | ~$1.50 per resolution | ~$0.05/resolution typical (Gemini Flash-Lite, BYO) + $0 platform fee |
| Cost (self-hosted) | Not available | Free — open source, bring your own LLM keys |
| Seat fees | Yes — per-agent pricing tiers | No — no platform seat fees |
Key differences
Where resolution happens
Zendesk AI is built on top of a ticketing system. Even its AI features route through the ticket workflow — classify, suggest responses, automate routing. The issue still becomes a ticket. ResolveKit resolves issues inside your app before they ever reach the helpdesk. For mobile-first companies, this means users never leave the app to find help.
Approval & safety
Zendesk AI can suggest responses and auto-classify tickets. But it cannot safely execute actions with user consent. ResolveKit's approval system lets agents propose and execute actions with explicit guardrails — every action goes through a policy-defined approval flow before it runs.
Cost at scale
Zendesk AI costs approximately $1.50 per resolution, plus seat-based pricing for agents. ResolveKit has no platform fee per resolution or per seat. With bring-your-own keys, teams often land around $0.05 per resolution on Gemini Flash-Lite. It is open source and can run self-hosted or on ResolveKit-managed infrastructure.
Open source & self-hosting
Zendesk is a fully proprietary cloud platform. ResolveKit is AGPL-3.0 open source — you can inspect, modify, and run it entirely on your own infrastructure. SDKs are MIT licensed, so you can use them in any project, commercial or otherwise.
Can you use both?
Yes — they sit at different stages of the support funnel. ResolveKit is the first line of defense, resolving issues in-app before they escalate. Zendesk is the escalation path for complex cases that need human agents, SLA tracking, and omnichannel management. Teams using both see ResolveKit deflect 30-50% of repeatable issues before they reach Zendesk.
Which should you choose?
Choose Zendesk AI if...
- • You need a full helpdesk platform with ticket management, SLAs, and reporting
- • Your team already uses Zendesk across multiple channels (email, chat, phone)
- • Your primary support surface is web or email, not in-product
- • You don't need AI agents to execute actions inside your product
Choose ResolveKit if...
- • You have a native iOS or Android app with significant in-app support volume
- • Users get stuck in-product and leave before contacting support
- • You want AI that resolves issues in-app, not just routes them to agents
- • You need approval guardrails and full audit trails for AI actions
- • Open source and self-hosting are requirements, not nice-to-haves