Resolve vs Jira Service Management

JSM brings request management, change and incident workflows, and deep integration with Jira and the Atlassian suite. For engineering and IT teams it is powerful. The wall is who is allowed to change things.

Basic changes require admin access. As one G2 reviewer put it, on JSM workflow changes "require admin access." The people closest to the support work often cannot adjust it themselves.

Setup demands specialized knowledge. Reviewers describe JSM setup as "difficult without prior experience... often requiring JQL knowledge, admin skills," with "smaller teams frequently hiring consultants." That is a real barrier for a team that just wants to answer customers.

It is ITSM-shaped, not resolution-shaped. JSM is oriented around tickets, queues, and process. AI features exist, but the platform is designed for structured internal service management, not for an AI that resolves the bulk of external customer tickets on its own.

Resolve starts from a different premise: the AI is the product, not a widget bolted onto a ticketing system. Every ticket runs a resolution engine on arrival. It is categorized, matched to the customer's full history, grounded in your knowledge base, and scored against a confidence threshold you control. When the answer is confident and low risk, Resolve resolves it with zero human involvement. Everything else comes to you as a clean decision card.

The design intent is 80 to 90 percent of tickets auto-resolved, but the number that matters is verified resolution, not deflection. Resolve grounds every answer in real content or live system data and refuses to guess when it cannot. A separate supervisor model verifies each reply before it ships. Business logic like refund amounts and return windows is computed in code, never authored by the language model. Reopen rate is treated as the honesty north star, so "the customer never reached a human" is never allowed to masquerade as "solved."

The four things Resolve does differently

• Flat pricing that never taxes success. No per-agent seats and no per-resolution meter. Your bill does not climb when the AI does its job better.
• Verified resolution, not deflection. Grounded answers with cited sources, a supervisor check before send, and reopen rate reported honestly next to any deflection number.
• Zero-admin configuration. Change routing, tone, SLAs, and the confidence dial in plain language. No admin role gate, no query language, no consultant.
• A self-improving knowledge base. Resolved tickets auto-draft articles that a human approves before they become groundable, so the next similar ticket resolves alone and a bad answer never becomes a cited source.

• Pricing model: per-agent tiers within the Atlassian ecosystem vs Resolve: flat rate, no per-seat
• Real resolution rate: process and queue management, AI at the edges vs Resolve: AI resolves by default, grounded and cited, designed for 80 to 90 percent
• Setup time: often requires JQL, admin skills, or a consultant vs Resolve: live in minutes, no query language
• Admin needs: basic changes gated behind an admin role vs Resolve: zero-admin, anyone can tune it in plain language
• Who it is for: IT and engineering teams doing structured ITSM in Atlassian vs Resolve: customer-support teams that want AI to resolve and no admin gate

JSM is the right tool if you are doing internal IT service management, change and incident workflows tied to engineering, and you already run on Jira and Confluence. The tight link between service requests and developer work is a genuine advantage that a customer-support-focused tool will not replicate. If your team already has Jira admins and JQL fluency, the admin gating is less of a burden. Resolve is the better pick for external customer support where you want AI to resolve most tickets and you do not want basic changes locked behind an admin role.