Developer Tools
Jira
Connect your AI to Jira
Scrum masters and project managers live inside Jira's customizable workflows, sprints, and backlogs. Adjacent teams need that same data to make decisions, but Jira's permission schemes, custom field sprawl, and JQL dependency create more noise than insight.
Why it matters
Capabilities that matter most for Jira
01
Jira without JQL
Issues, sprints and boards become lists with clean labelled fields, so adjacent teams can filter them without learning JQL or custom field ids.
02
Issues beside support and revenue
Join Jira issues with helpdesk or CRM lists to see which customers and deals are waiting on which tickets.
03
Governed AI for delivery
AI tools answer within per-user and per-team security, and change issues only through approved actions.
Use cases
Example AI Use Cases for Jira
scenario
-
Creates a Jira issue from a Zendesk ticket.
What popdock provides
--
From a Zendesk ticket, PopdockAI opens a matching Jira issue with the summary, description, and links carried across, so engineering gets the full context without a support agent retyping it.
Business outcome
---
Bugs and requests raised in support reach engineering in minutes, with nothing lost in the hand-off.
scenario
-
When an error lands, someone has to own it in Bugsnag and someone has to own the Jira issue that tracks it, and those are often set separately by different people. Matching the same person across both systems by hand means looking up their account in each, and the error ends up with one engineer while the issue sits with another.
What popdock provides
--
Give an error and the owner's email address, and it finds that person in both Bugsnag and Jira by email, then finds the Jira issue that tracks the error. You see the error, the issue key, the person and both current assignees, and nothing is assigned until you approve. If the email matches more than one person it stops and lists them, and if either record already has an assignee it asks before reassigning. When the person or the issue is missing on one side, it assigns the other half and tells you plainly which half was skipped, without granting access or changing status.
Business outcome
---
One engineer owns the error and its Jira issue together, so nobody assumes someone else is handling it.
scenario
-
Judging a release means pulling its session and error numbers from Bugsnag, working out which errors really happened on that build, and then scanning Jira for the work that shipped around the same time. Errors from older builds get blamed on the new one, and Jira issues that merely moved that week get presented as related.
What popdock provides
--
Name the app version, the Bugsnag project and the Jira project, and it reads the release's sessions and unhandled rate, then checks events to confirm which errors actually occurred on that build. Jira issues updated since the release are read alongside, and only an issue whose summary carries an error id counts as a confirmed link; everything else is labelled as date-window context. Each confirmed error is marked tracked or untracked in Jira, and where the previous release can be read it says whether this one looks better or worse. Nothing in either system is changed.
Business outcome
---
You get an honest picture of what a release broke and what is being tracked, without mistaking coincidence for cause.
scenario
-
Assigning an error and its Jira issue to the same person only works if that person exists and is active in both systems. When emails differ or a Jira account is deactivated, assignments quietly fail and nobody notices until something goes unowned.
What popdock provides
--
Name the Bugsnag project, and it lists the project's collaborators with their roles and invitation status, then looks each one up in Jira by email, never by display name, along with any Jira team membership. You get three groups: matched and active, matched but inactive in Jira, and no Jira user, with pending Bugsnag invitations shown as their own state. Blank emails are reported as unmatchable rather than skipped, and multiple Jira matches are all listed. It only reads, and checks the Jira side is connected before reporting a total mismatch.
Business outcome
---
You fix ownership gaps between Bugsnag and Jira before an assignment silently fails.
scenario
-
A busy Bugsnag project builds a backlog of high-volume errors that nobody ever raised in Jira. Catching up by hand means checking each one for an existing issue, then creating and linking issues, and raising too many at once floods the board.
What popdock provides
--
Set the Bugsnag project, the Jira project, a minimum event count and a cap, and it finds open errors above the threshold and drops any already tracked by a Jira link or an issue mentioning the error id. It confirms the Bug issue type exists, then shows the capped list for your approval. For each approved error it re-checks for duplicates, creates the issue, reads it back, adds a detail comment and links it to the error. The run stops at the first failure or unverified write, never exceeds the cap, and leaves Bugsnag untouched.
Business outcome
---
Your untracked error backlog is caught up in one controlled pass, without duplicates or a flooded board.
scenario
-
A Jira issue tracking an error quickly falls out of date: the error keeps firing and more users are affected, but the issue still reads as it did when it was raised. Copying the current numbers and sample events across by hand rarely happens.
What popdock provides
--
Give the Bugsnag error, the Jira project and how many recent occurrences to sample, and it reads the error's status, severity, events, users, dates and stages, plus a sample of recent events. It finds the Jira issue that tracks it, asking which one if several match. You see the comment and the issue key before it posts exactly one comment, and it never edits anyone else's. Afterwards it flags a mismatch when the issue is done but the error is still open, or the reverse, without changing either.
Business outcome
---
Jira issues stay honest about live errors, and mismatched statuses are spotted without anyone digging.
scenario
-
You need to know which open Bugsnag errors are tracked in Jira and which are not, but the link may live in a remote link or only in an issue summary. Searching error by error is slow, and an issue whose wording only looks similar gives false comfort that the error is covered.
What popdock provides
--
Name the Bugsnag project, the Jira project and optionally a severity, and it reads the open errors, busiest first. Each one is looked up in Jira by remote link and then by issue summary, and it counts as tracked only when the error id appears in one of those, never from similar wording. You get tracked and untracked tables sorted by events, ending with the untracked error to raise first. It only reads, reports a link with no nameable issue as tracked with the key unknown, and checks the project key is right before calling everything untracked.
Business outcome
---
You see exactly which errors lack a Jira issue, so nothing important goes unrecorded.
scenario
-
Raising a Jira issue for a Bugsnag error by hand means copying the detail across, checking nobody already raised one, and linking the two so each side can find the other. Miss the check and you get duplicates; skip the link and the error and issue drift apart.
What popdock provides
--
Give the Bugsnag error, the Jira project and the issue type, and optionally your Jira site address, and it reads the error and checks Jira for an existing remote link or issue first, stopping if one exists. It confirms the project and issue type, shows you the summary and waits for approval, then creates one issue, reads it back and adds the detail as a comment. The issue is linked to the error in Jira and, when you supplied the site address, back from Bugsnag. If the read-back fails it stops before linking and never creates a second issue.
Business outcome
---
Each error gets one Jira issue, linked both ways, so engineers and the board share the same picture.
scenario
-
Jira bugs raised from Ghost Inspector failures stay open long after the test starts passing, because someone has to check each test's recent history first. The backlog fills with bugs that are really fixed, hiding the ones that still need someone's attention.
What popdock provides
--
Name the Jira project and a stable period, and it finds open bugs raised from Ghost Inspector failures and reads each test's runs in that period. A bug becomes a close-out candidate only with at least three runs that all passed, and bugs still failing or lacking evidence are listed separately. Duplicate bugs for one test are flagged. Verification comments are posted only if you ask and confirm the list. It never closes or reassigns an issue and never reruns a test.
Business outcome
---
Fixed bugs are flagged for closure with real run evidence, and the backlog shrinks to work that still matters.
scenario
-
Raising a useful Jira bug from a Ghost Inspector failure means copying the failing step, the console errors and the run details, then checking nobody has filed it already. Linking the bug and the test result both ways is the step that usually gets skipped.
What popdock provides
--
Give the test result and the Jira project, and it confirms the run really failed, then gathers the first failing step and console errors. It checks the result's comments and Jira for an open bug on the same test and stops if one exists. You see the summary and evidence, and nothing is written until you confirm. It creates the bug once, adds the evidence as a comment and a link to the result, and comments the Jira key on the test result. Any link that fails is named.
Business outcome
---
Every test failure becomes one well-evidenced Jira bug, linked both ways, with no duplicates.
scenario
-
Test failures pile up in Ghost Inspector while the Jira backlog tracks only some of them. Working out which failures nobody has ticketed, and which open bugs are for tests that now pass, means cross-checking every failing test name against the backlog by hand.
What popdock provides
--
Name the Jira project and a lookback period, and optionally a suite, and it groups recent Ghost Inspector failures by test so repeated failures count once. Each is checked against open Jira bugs, retrying with a shorter fragment before calling it untracked. It also finds open bugs whose test is no longer failing. When Jira returns nothing at all it checks the project key first. Nothing is created or changed in either system.
Business outcome
---
Untracked failures and stale bugs come out in one report, so nothing falls between testing and the backlog.
scenario
-
A suite's pass rate tells you something is wrong, but not whether anyone owns it. Seeing which failing tests have an open Jira bug and an assignee means combining weeks of run history with Jira backlog searches, one test at a time.
What popdock provides
--
Name the suite and the Jira project, and it reads the suite's runs for pass rate and direction, then each test's failure rate, showing a rate only with at least three runs. Every failing test is matched to open Jira bugs with status and assignee. You get a worst-first table, a note when failures sit on one browser or region, and a ranked list that puts untracked tests failing most of the time at the top. Nothing in Ghost Inspector or Jira is changed.
Business outcome
---
You see which failing tests have no owner, and fix the costliest gaps first.
scenario
-
A test that keeps failing often has history: earlier Jira bugs, comments with conclusions, and a known product issue behind it. Without that context people repeat an investigation someone already finished, and reach the same conclusion a second time.
What popdock provides
--
Name the test and the Jira project, and it reads the test's settings and run history and names the failure pattern as browser-specific, clustered in time or steady. It reads the latest failing step, console errors and any notes on the result. It then reads every Jira bug mentioning the test, the comment history of the latest one, and bugs about the page the failing step targets. Disagreements, such as a Done bug while the test still fails, lead the report. Causes are asserted only with evidence, and nothing is changed.
Business outcome
---
You start from everything already known about a failing test, instead of repeating work someone finished last month.
scenario
-
Before a Jira bug is closed, someone should rerun the Ghost Inspector test it came from and record the result. Finding that test from the bug, running it and writing up the outcome is tedious, so bugs get closed on trust and some of them come back.
What popdock provides
--
Give the Jira issue key and it reads the bug, finding its test from the summary, an earlier comment or a name you supply, and stops rather than guess when several tests match. It asks first if the bug is already closed. The test runs once, and if it fails the first failing step and console errors are collected. One verification comment goes on the bug, and an inconclusive run posts nothing. It never changes the bug's status.
Business outcome
---
Bug fixes are proven with a fresh test run before closure, with the evidence on the Jira issue.
scenario
-
When a GitHub Actions build fails on a feature branch, the Jira issue for that work rarely hears about it. Linking them means spotting the Jira key in the branch or commit message, opening the issue in Jira and pasting the run details by hand.
What popdock provides
--
Name the repository, the Jira project and a lookback period, and it finds the newest failed run per branch and reads a Jira key from the branch, then the commit message. Each key is confirmed in Jira, closed issues are skipped, and issues already commented with that run are skipped so nothing posts twice. You see the proposed comments and unmatched runs, and nothing is posted until you confirm. Each comment names the workflow, branch, run, commit and author.
Business outcome
---
Jira issues learn about their failed builds automatically, without duplicate comments or noise on closed work.
scenario
-
Escalating a GitHub issue into Jira means creating the ticket, adding a link back to GitHub and noting the Jira key on the GitHub issue. Skip the check and the same issue gets escalated twice by different people on different days.
What popdock provides
--
Give the GitHub issue number and the Jira project, and it reads the issue and checks Jira for an existing link to it, stopping if there is one and listing similar summaries for you to judge. It resolves the project and issue type and shows the Jira summary, and nothing is created until you confirm. It creates the issue once, links it to GitHub and comments the Jira key on the GitHub issue, naming any step that failed. It says that the GitHub body is not copied.
Business outcome
---
GitHub issues reach Jira once, linked both ways, so engineering and planning track the same work.
scenario
-
Work that lands in GitHub without a Jira key is invisible to planning and reporting, and commits that cite a key that does not exist mislead everyone. Checking means reading every commit message and validating each key against Jira by hand.
What popdock provides
--
Name the repository, the Jira project and a lookback period, and it reads commits, ignoring merges, and pulls out the Jira keys. Each key is checked against the project to separate tracked commits, untracked commits and dangling references to issues that do not exist. Untracked commits are grouped by author with their Jira user. If no commit carries any key it says the team may not use keys rather than flagging everything. Nothing is created.
Business outcome
---
Untracked work and broken Jira references come to light, so planning reflects what was actually built.
scenario
-
Jira says an issue is Done but no code references it, or it is still To Do while commits pile up against it, or it has sat In Progress with no commits for weeks. Spotting these mismatches means comparing every issue's status with the GitHub commit log by hand, issue by issue.
What popdock provides
--
Name the Jira project, the repository and a lookback period, and it reads recently updated Jira issues and the GitHub commits for the same window in one pass. Keys are matched exactly so ABC-12 never matches ABC-123. Each issue is classed as Done with no commits, not started with commits, stalled in progress or consistent, by the meaning of its status, and statuses it cannot place are listed. Truncated commit lists are flagged. Status changes are suggested, never made.
Business outcome
---
Board status matches the code, with stalled and mislabelled issues called out for the next stand-up.
scenario
-
Teams agree that GitHub issues with a certain label should be tracked in Jira, then copy them across by hand when they remember. Some are missed entirely, others are copied twice, and the links between the two systems are rarely added.
What popdock provides
--
Name the label, the repository and the Jira project, and it reads open GitHub issues with that label and checks every existing GitHub link in Jira to find the ones not yet synced. You see the gap and confirm all or some of them before anything is created, up to 20 per run. Each gets one Jira issue, a link back to GitHub and a comment with the Jira key. If the link check fails it stops, since that is what prevents duplicates.
Business outcome
---
Labelled GitHub issues reach Jira reliably, each exactly once, with links in both directions.
scenario
-
Answering what code exists for a Jira issue means searching GitHub branches, commits, issues and workflow runs for its key, then checking who wrote the code. Partial key matches, and a Done issue whose branch build is failing, are easy to miss along the way.
What popdock provides
--
Give the Jira issue key and it reads the issue, then finds every GitHub branch, commit and issue that references the key exactly, discarding partial matches, plus each branch's latest workflow runs. Commit authors are mapped to Jira users. Mismatches are called out, such as a Done issue whose branch build is failing, a To Do issue with commits, or commits that exclude the assignee. No references is reported as a result, not an error. Nothing in GitHub or Jira is changed.
Business outcome
---
You see all the code behind a Jira issue in one view, with status mismatches flagged.
scenario
-
Jira projects fill up with issues nobody has touched in weeks, open work with no owner and due dates that passed quietly. Finding them means building filters, scrolling long lists and deciding which kind of mess is the real problem, so the cleanup keeps getting put off.
What popdock provides
--
Name the Jira project, and optionally how many days counts as stale, and it sweeps every open issue into four groups: untouched too long, no assignee, past due and in progress without an estimate. Each group is a table sorted worst first, with a count, and an empty group is shown as none rather than left out. A missing due date is never treated as overdue. It closes with which problem matters most and the one action that would clear most of it, and it changes nothing in Jira.
Business outcome
---
Your project gets a clear hygiene report and a single next step, so backlog cleanup actually happens.
scenario
-
Creating a Jira issue properly means picking the right project, an issue type that exists in that project and the correct assignee from a list of similar names. Get one of them wrong and the issue is rejected, lands in the wrong place or sits unassigned.
What popdock provides
--
Give the project, a summary, the issue type and optionally an assignee and due date, and it looks each one up in Jira before writing anything. If the project or person matches more than one record it lists them and stops, if the issue type is not in that project it shows the types that are, and an unknown assignee stops it rather than leaving the issue unowned. You see the full details and confirm, the issue is created once, and its new key is reported back.
Business outcome
---
New issues land in the right project with the right type and owner, without rejected or misfiled tickets.
scenario
-
Understanding why a Jira issue is stuck means reading its detail, scrolling the comments, checking logged time, opening subtasks and following links to other systems. It is slow enough that people ask in chat instead and get half the story.
What popdock provides
--
Name the issue, and it gathers its status, people and dates, the recent comments in date order, time logged and by whom, subtasks and their status, attachments and links out to other systems. You get a short summary of where it stands, a timeline of the last five comments, and a closing line on what appears to be blocking it. Comments are quoted rather than stretched into conclusions, empty sections are said plainly, and nothing in Jira is changed.
Business outcome
---
You understand where any issue stands and what is holding it up in one read, without clicking through every tab.
scenario
-
Writing a status update for a Jira project means counting what was raised, what moved and what finished, then working out whether intake is outrunning delivery. Pulling that together from filters every week eats time that should go into the work.
What popdock provides
--
Name the project and a date range, and it reports what was raised, broken down by issue type and reporter, what saw activity, broken down by status, what was completed, and what is still open with the oldest items. It closes with a short note on whether new work is outpacing completion and where it is sitting. It says when counts are a floor because a limit was hit, explains that completion is inferred from status, and changes nothing.
Business outcome
---
Stand-ups and status updates write themselves from real project numbers instead of a weekly filter exercise.
scenario
-
Seeing where time went in Jira usually means exporting worklogs and pivoting them by person, issue and day. Large entries, days with nothing logged and time against unknown issues are easy to miss in raw rows.
What popdock provides
--
Give a date range, and optionally a person, and it totals the time logged in Jira in hours, then breaks it down by author, by issue and by day so gaps are visible. Issues are named where they can be resolved and otherwise shown by their ID with the reason, never guessed. It notes anything unusual, such as one very large entry or a day with nothing logged. It reports on time only and does not record or change any worklog.
Business outcome
---
You see who logged what time against which work, with unusual entries flagged, without building a spreadsheet.
scenario
-
Logging time in Jira after the fact is where double booking happens: you cannot remember whether you already logged yesterday's work, or you log against an issue that was closed last week. Fixing a wrong worklog later is more work than logging it once.
What popdock provides
--
Give the issue, the time spent, a date and a note, and it confirms the issue exists in Jira and asks first if it is already closed. It shows the time already logged and points out any entry by the same person on the same date so you can say whether it is a duplicate. You confirm the details and the time is logged once, in Jira's own duration format, leaving the remaining estimate alone unless you ask. The new entry and the updated total are read back.
Business outcome
---
Your time is booked once against the right issue, with no duplicate worklogs to clean up later.
scenario
-
Before handing someone more Jira work, a lead wants to know what they already carry across every project. That means filtering by assignee, adding up story points, spotting overdue and forgotten items, and still missing what the person is waiting on from others.
What popdock provides
--
Name the person or their email, and it finds them in Jira and lists their open assigned issues across projects with status, due date and story points. Totals show the open count, points, past due and untouched for over two weeks, plus what they raised that is still open and which teams they belong to. A short verdict says whether the load looks heavy and which issues to move first. It looks at one person only, recommends rather than reassigns, and changes nothing.
Business outcome
---
Leads rebalance work based on what each person actually carries, before deadlines start slipping.
scenario
-
Setting up a Jira project means checking the key is free, choosing a lead from similar names and filling in the details. Create one with a key already in use and it fails; update the wrong one and you rename someone else's project.
What popdock provides
--
Give the project name, key, lead and description, and it checks Jira for the key and the name to decide whether this is a new project or an update. The lead must match exactly one person, and an unknown lead stops it rather than creating a leaderless project. If the key exists under a different name it asks which is right. You see whether it will create or update and the values, and confirm before one write, with an update sending only fields that change. The stored project is then read back.
Business outcome
---
Projects are created or updated correctly the first time, without key clashes or renaming the wrong project.
scenario
-
Handing a Jira issue to someone else sounds quick, but you need to check who has it now, find the right person among similar names and leave a note saying why. Skip the note and the new owner has no context; skip the check and you take work off someone mid-task.
What popdock provides
--
Name the issue, the new assignee and a reason, and it reads the issue first and asks before taking it off someone else. The assignee must match exactly one active person in Jira. You see the current and new owner and the handover comment, and confirm before anything changes. The issue is assigned once, then the comment is added only if the assignment worked, and with no reason given the note stays a plain handover rather than an invented justification. The new assignee is read back.
Business outcome
---
Work changes hands with a clear handover note, and nobody loses an issue they were working on without warning.
scenario
-
A long Jira backlog makes it hard to see what to pick up next: overdue items sit next to old ideas, and unassigned urgent work hides among stale tickets. Sorting it by hand every sprint takes time the team does not have.
What popdock provides
--
Name the project, and optionally a status and how recent counts as active, and it reads the open issues and ranks them on due dates, ownership, age, staleness and size. Past-due work comes first, then unassigned work that is still live, then the oldest stale items. You get a table of up to 20 issues and a short recommendation of the top three with reasons, plus anything unassigned that looks urgent. It ranks only on what the issues contain, says when data is thin, and changes nothing.
Business outcome
---
Your team starts each sprint with a ranked shortlist and clear reasons, instead of debating the whole backlog.
scenario
-
Engineering prioritizes Jira bugs without knowing how many customers are hitting them, because the evidence sits in Zendesk tickets. Searching tickets by keyword and counting organizations by hand is slow and usually skipped.
What popdock provides
--
Name the Jira issue, and it reads its summary and finds the ticket it came from if there is one, then searches recent Zendesk tickets on a few distinctive terms from the summary. Each candidate is checked by subject, kept or rejected with a reason, then grouped by organization with bad satisfaction ratings counted. You get totals, a table by organization and a low, medium or high impact rating with the reason. It says that subject matching is an estimate, lists the terms searched, and changes nothing.
Business outcome
---
Bugs are prioritized on real customer impact, with the affected organizations named, instead of on gut feel.
scenario
-
When a customer asks about an escalated problem, the agent has to find the linked Jira issue, read its status and comments, and translate engineering detail into something the customer can understand. Each update takes a trip into a system support may barely know.
What popdock provides
--
Give the Zendesk ticket, and it finds the linked Jira issues from the ticket's internal notes and the issue summaries, listing broken links rather than dropping them. For each issue you get status, assignee, due date, last update and a summary of the latest comment, with a flag when the ticket and issue disagree on whether the work is finished. It drafts a short plain-language reply with no internal names or estimates the comments do not support. The draft is shown to you only, and nothing is posted or changed.
Business outcome
---
Agents give customers an accurate escalation update in minutes, without chasing engineering for status.
scenario
-
Escalating a Zendesk ticket to engineering means copying details into a new Jira issue, linking the two and noting the escalation on the ticket. Done by hand, the same ticket gets escalated twice, or the link is missing on one side and nobody can follow it later.
What popdock provides
--
Give the ticket, a Jira project and optionally an issue type, and it reads the ticket and its conversation, then checks both systems for an existing escalation and stops if it finds one. You see the issue summary, which starts with the ticket number, and a short description drawn from the ticket, and confirm before anything is created. The issue is created once, given the context as a comment and a link back to the ticket where possible, and an internal note naming the issue goes on the ticket. No public reply is posted and the ticket's status is left alone.
Business outcome
---
Escalations reach engineering once, with full context and a two-way link that support and developers can both follow.
scenario
-
When a support ticket turns out to be about a bug engineering already tracks, the two records should point at each other. Linking them by hand means notes in two systems, and it is easy to link the same pair twice or only on one side.
What popdock provides
--
Give the Zendesk ticket and the Jira issue, and it confirms both exist and checks the ticket's internal notes for an existing link, stopping if they are already linked. You see the ticket subject and issue summary side by side and confirm before anything is written. It adds an internal note on the ticket, a comment on the issue with the ticket details and a link back where possible. If one side fails it reports the half-made link so you only retry that part, and nothing public is posted.
Business outcome
---
Support and engineering can follow the same problem from either side, with no duplicate or one-way links.
scenario
-
Escalations from Zendesk need a Jira account to assign or report against, but nobody keeps a list of which agents have one. Checking each agent's email in Jira by hand is tedious, and matching on names alone pairs the wrong people.
What popdock provides
--
Name a Zendesk group, or check all agents and admins, and it looks up each agent's email in Jira. Agents are sorted into matched, inactive in Jira, no Jira account and email matches whose names differ enough to check by eye, with counts for each. Matching is on email only, never on name. If Jira returns nothing for most agents it explains that privacy settings likely hide their email, and nothing is changed in either system.
Business outcome
---
You know which support agents can be assigned escalations in Jira and who still needs an account.
scenario
-
Escalated tickets and their Jira issues drift apart: a fix ships but the customer is never told, or the ticket is closed while engineering is still working. Spotting these means comparing statuses across two systems one pair at a time.
What popdock provides
--
Name the Jira project and a lookback period, and it reads recently updated escalated issues, finds each one's Zendesk ticket, and compares their status. Pairs are sorted into customers waiting on a finished fix, tickets closed too early, orphans whose ticket cannot be found, and urgent tickets whose issue has no assignee, with consistent pairs counted. Customers waiting on a finished fix come first. It notes that links made only on the ticket side are not found, and changes nothing.
Business outcome
---
Customers waiting on fixes that already shipped are found and told, and tickets are not closed before the work is done.
scenario
-
When engineering finishes a fix in Jira, the Zendesk ticket waiting on it often sits untouched for days because support never hears about it. Checking finished issues against open tickets and writing up the outcome is a manual job that falls through the cracks.
What popdock provides
--
Name the Jira project and a lookback period, and it finds escalated issues finished recently whose Zendesk ticket is still open, using the latest Jira comment as the resolution. You see each pair with a one-line resolution and can drop rows before confirming. Each confirmed ticket gets an internal note with the issue, status and outcome; status moves to pending only if you ask, and never to solved or closed. Customers are not contacted, an agent does that, and Jira is never changed.
Business outcome
---
Agents learn about finished fixes straight away, so waiting customers hear back sooner.
scenario
-
Change managers approve ServiceNow changes without knowing whether the development work behind them is finished in Jira. Checking means searching Jira for each change number, reading each issue status and chasing developers, so changes go ahead with work still open or are delayed for work that was done days ago.
What popdock provides
--
Give a window of days, and optionally an assignment group and Jira project, and it reads the ServiceNow change requests planned to start in that window and finds the Jira issues that carry each change number in their summary or labels. Each change is sorted into ready, at risk or no Jira work found, with its approval, risk, open change tasks and the unfinished Jira issues with status and assignee. It only reads, so nothing is changed in either system.
Business outcome
---
Change approvals are based on the real state of the Jira work, and at-risk changes surface days before they start.
scenario
-
Escalating a ServiceNow incident or problem to development means writing a Jira issue by hand, finding the right project and issue type, looking up the assignee in Jira, and remembering to note the Jira key back in ServiceNow. Steps get skipped, so the same incident is escalated twice or the service desk cannot see where it went.
What popdock provides
--
Give a ServiceNow incident or problem number and a Jira project, and it reads the record, then checks Jira for an issue that already carries that number and stops if it finds one. It resolves the issue type and maps the ServiceNow assignee to a Jira user by email, leaving the issue unassigned when there is no match. You see the issue it will create and nothing is written until you confirm. It then creates the Jira issue, adds a comment with the ServiceNow details and records the Jira key as a work note on the ServiceNow record.
Business outcome
---
Every escalation lands in Jira once, with full context, and the service desk can see exactly where it went.
scenario
-
Once an incident or problem is escalated from ServiceNow to Jira, nobody watches the pair. Jira issues go quiet while the ServiceNow record stays open, or one side is closed and the other is forgotten, and finding them means checking every escalated record in both systems by hand.
What popdock provides
--
Give a number of days, and optionally a Jira project and ServiceNow assignment group, and it finds Jira issues that carry a ServiceNow number in their summary and reads each ServiceNow record. Each pair is placed in one bucket: stale, done in Jira but open in ServiceNow, or closed in ServiceNow but open in Jira. Stale issues show their latest Jira comment and author, and Jira issues pointing at records that do not exist are reported too. It only reads, so nothing is changed in either system.
Business outcome
---
Escalations that have stalled or fallen out of step are caught and closed instead of lingering for weeks.
scenario
-
When a release is ready, someone has to raise a ServiceNow change, list every Jira issue it deploys and tag each issue with the change number. Doing it by hand means issues are missed, the same work is put on two changes, and the audit trail between Jira and ServiceNow is incomplete.
What popdock provides
--
Give a Jira project, or a list of issue keys, and a planned start date, and it collects the finished Jira issues, setting aside any already tagged with a change number. It checks ServiceNow for an open change covering the same project and asks before raising another. You see the draft change and the issues it will tag, and nothing is written until you confirm. It then creates the change once, reads back its number and comments that number on each Jira issue.
Business outcome
---
Every release has one ServiceNow change listing exactly what it deploys, with matching references in Jira.
scenario
-
Priority 1 incidents and problems in ServiceNow depend on fixes tracked in Jira, but the service desk cannot see whether that work is assigned, on schedule or even raised. Answering it for a review means looking up each P1 in Jira and adding up the open work by hand.
What popdock provides
--
Give a lookback period, and optionally a Jira project, and it reads open priority 1 incidents and problems in ServiceNow and finds the Jira issues carrying each record number. You get the development work behind each P1 with status, assignee, due date and story points, with overdue and unassigned issues flagged, and a separate list of P1s with no Jira issue at all. Totals show the open P1 count and the story points still open. It only reads, so nothing is changed in either system.
Business outcome
---
Major incident reviews see the real development backlog, and P1s without a fix in progress are caught.
scenario
-
Once an incident is escalated to Jira, the service desk keeps asking development for updates because ServiceNow shows nothing of the Jira work. Developers do not update both systems, so callers are given stale answers and analysts open Jira to find out.
What popdock provides
--
Give a ServiceNow incident or problem number, and it finds the Jira issue carrying that number and reads its status, assignee, due date, latest comments and open subtasks. It drafts a short work note and shows it to you, and nothing is written until you confirm. The note is then added once to the ServiceNow record. If the Jira work is done but the record is still open it tells you, but it never changes the record's state.
Business outcome
---
The service desk sees development progress in ServiceNow without chasing developers or opening Jira.
scenario
-
To see what one person really has on their plate, you open BugHerd and Jira separately, find them in each, filter to their open items and add the lists together. Items sent from one system to the other show up twice, so the total looks heavier than it is, and overdue work in either tool is easy to miss.
What popdock provides
--
Give a person's email, and optionally a Jira project key, and it finds that person in both BugHerd and Jira by email. It reads their open BugHerd tasks and open Jira issues, drops anything done or closed, and counts a linked task and issue once so nothing is double counted. You get totals for each system and combined, the overdue items on either side, and one table of all open work. It only reads, so nothing is changed in either system.
Business outcome
---
A true picture of one person's workload across BugHerd and Jira, with no double counting and nothing changed.
scenario
-
Once a BugHerd task and a Jira issue are linked, their statuses drift. A developer closes the issue but the task stays open on the site, or the web team finishes a task while the Jira issue sits stale. Finding these pairs means opening each link on both sides and comparing statuses by hand.
What popdock provides
--
Name the BugHerd project and the Jira project key, and optionally a lookback period, 90 days by default, and it collects the links from both sides, including archived BugHerd tasks. It reads the other half of each pair and sorts them into in step, done in Jira but open in BugHerd, done in BugHerd but open in Jira, and broken links. You get a table for each problem class and a count of the pairs in step. It only reads, so nothing is changed in either system.
Business outcome
---
See every linked BugHerd task and Jira issue that has drifted, so fixes get verified and stale issues get closed.
scenario
-
Moving a website bug from BugHerd to Jira by hand means creating the issue in the right project and type, copying the description, page and severity, finding the assignee in Jira, and then linking the two. Miss the duplicate check and the developers get two issues; miss the link and nobody can trace the issue back to the page.
What popdock provides
--
Name the BugHerd project and task, the Jira project key and optionally the issue type, Bug by default, and it reads the task and checks Jira for an issue already sent from it. It resolves the project and issue type, and matches the BugHerd assignee to a Jira user by email, leaving the issue unassigned when there is no single match. You see the issue before anything is created and nothing is written until you confirm. Then it creates the issue with the due date, adds the description, a remote link to the task and a comment on the BugHerd task, and reports which steps succeeded.
Business outcome
---
Website bugs reach developers in Jira once, with full detail and a link back to the BugHerd task.
scenario
-
When a developer finishes a Jira issue, the linked BugHerd task often stays open on the site, and when the web team closes a task, the Jira issue lingers. Fixing each pair means opening both records, updating the task and leaving comments, one link at a time.
What popdock provides
--
Name the BugHerd project and the Jira project key, and it finds the linked pairs where only one side is finished. For a Jira issue that is done, it proposes marking the BugHerd task done with a comment; for a BugHerd task that is done, it proposes a Jira comment asking the team to verify and close, and leaves the Jira status to the Jira workflow. You see every proposal in one table and only the rows you approve are applied. It never reopens anything, and it reports what changed on each side and anything that failed.
Business outcome
---
Linked BugHerd tasks and Jira issues back in step, with only the changes you approve applied.
No items found.
Ready to unlock your data?
Start building tools that turn your business systems into AI superpowers
Join forward-thinking companies that are transforming their operations with intelligent, secure AI automation.