Second Chance. No AI, no black box.Free and live on the Atlassian Marketplace

Self-service doesn't end at submission.

The moment a request is submitted, Second Chance reviews it against your connected Confluence knowledge base and surfaces the articles that actually match, ranked by confidence, giving users one more chance to self-resolve before an agent picks it up.

Forge-native. Read-only. It never touches your ticket lifecycle.

Second Chance requires Confluence connected as the Jira Service Management knowledge base.

Second Chance suggestion panel on a Jira Service Management issue, showing three knowledge base articles ranked weak, medium and strong.
Why after submission

Most knowledge tools fire when nobody's reading.

Jira Service Management suggests articles while a customer is filling in the form, before they've committed. By then most people have already decided they want a ticket, so the suggestions get skipped.

Native JSM · before

Suggestions during the form

Shown while the user is still typing, before they've committed to raising a request. Most are already set on a ticket, so the prompt is dismissed.

Second Chance · after

Suggestions after submission

Analysed once the request exists and the user has a ticket reference: the moment they're most open to a faster route to resolution.

How it works

Read the request. Score the knowledge. Rank the answers.

Deterministic keyword scoring: no LLMs, no embeddings, nothing to train. Every recommendation is inspectable.

01

Read the request

On the issue view, Second Chance reads the summary, description, request type and labels, as the viewing agent, so it only ever sees Confluence articles they can already access.

02

Score every candidate

It searches the Confluence space connected to the project as the customer-facing knowledge base, and scores each article on a transparent, weighted formula: request-type-in-title, keyword overlap, freshness.

03

Rank the top answers

The best three surface in the issue panel, each with a strength band and a plain-language reason. Requests with no strong match are logged as coverage gaps.

How the score is built

A weighted sum of signals. Deterministic, inspectable, and shown on every card.

Request type appears in the article title+30
Summary keyword overlap (×1.5 on a title hit)+25
Description keyword overlap+15
Label overlap · freshness+15 · ±3

Configured once, per project

The minimum match score and the weighting behind it live in Jira Service Management project settings, next to the rest of your JSM admin. Nothing to install or manage separately. Second Chance requires Confluence connected as the Jira Service Management knowledge base.

Second Chance settings screen in Jira Service Management project settings, showing the minimum match score and the scoring formula.

A genuine second chance to self-resolve

Matching articles surface right after the request is created, ranked by confidence, at the moment users are most likely to actually read them.

Catch known issues before an agent does

When a request matches an active incident or known problem, Second Chance flags it immediately with a status link, no waiting for triage.

See what your knowledge base actually covers

Analyse recent requests to find strong coverage, gaps, and recurring ticket types that deserve documentation. Turn deflection data into a roadmap.

Coverage intelligence

Every gap is a documentation opportunity.

Requests that arrive with no strong match are coverage gaps: the questions your Confluence knowledge base can't yet answer. Second Chance turns them into a ranked list of what to write next.

68%
Knowledge coverage
CoveredStrong match
PartialWeak / medium
No matchCoverage gap
Second Chance settings in Jira Service Management, showing Second Chance enabled with a minimum match score and scoring breakdown for a project.

Lives in Jira admin, not a separate app to manage

Second Chance is a free, standalone app for Jira Service Management, enabled per project in JSM settings. There's nothing to configure to get started, and tuning the match score is optional.

Confidence, at a glance

Every card says how sure it is, and why.

Strong
≥ 35

A confident match, usually the request type or key terms hitting the article title directly.

Medium
≥ 22

A reasonable match on keyword or label overlap, worth a look before escalating.

Weak
> 0

Some signal, but thin. Shown for transparency, never gate-kept, always labelled honestly.

Runs inside Atlassian
Runtime

Forge-native

Runs entirely inside Atlassian Cloud. No external servers.

Permissions

Reads as the agent

Agents only ever see Confluence articles they already have permission to read.

Data

Nothing leaves Atlassian

No LLMs, no embeddings, no learned models. Scoring is rules-based and auditable.

Lifecycle

Never touches tickets

It never changes states, workflows or request lifecycles. Read-only, always.

Give every request a second chance.

Install Second Chance free from the Atlassian Marketplace. It's read-only, Forge-native, and live on the next issue view.

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