When you plug a powerful multi-language translator right into Jira Service Management, you instantly bridge the communication gap between your support agents and your global customers. This is a game-changer. Suddenly, a single, skilled agent can field requests in dozens of languages, effectively turning your service desk into a lean, mean, global support machine.
The High Cost of Language Barriers in Jira

Before we even touch the configuration settings, let’s get real about the problem we’re solving. For any support team with a global footprint, managing a multilingual customer base without the right tools is a recipe for friction. It introduces a ton of hidden costs that go way beyond simple inconvenience.
Picture this: a SaaS company is crushing it, expanding into European and Asian markets. At first, it’s all high-fives and celebration. But then, the support tickets start rolling in—German, French, Japanese. The English-speaking support team, despite being experts at their jobs, becomes an instant bottleneck.
They find themselves stuck in a clumsy copy-paste dance with external web translators. This back-and-forth completely kills the natural flow of conversation and, worse, introduces massive delays.
The Domino Effect of Miscommunication
This manual process isn’t just slow; it’s riddled with risk. A tiny mistranslation of a key technical term can send an agent down the wrong troubleshooting rabbit hole for hours. Customers get more and more frustrated having to repeat themselves, and what should have been a five-minute fix spirals into a day-long ordeal.
This friction hammers your key performance indicators. First-response times creep up, resolution rates plummet, and customer satisfaction (CSAT) scores take a nosedive.
Now the company faces a tough choice: accept a lower standard of service in these exciting new markets or start the painfully slow and expensive process of hiring specialized agents for every single language. This is a classic growing pain for scaling businesses, a topic we explore in depth in our guide to multi-language support.
“The core issue isn’t a lack of skilled agents; it’s a communication barrier. Your best problem-solvers become ineffective if they can’t understand the customer’s problem in the first place.”
Quantifying the Business Impact
The need for good translation isn’t just a “nice-to-have.” It’s a massive economic driver. You just have to look at the global translation service market, which is projected to blow past USD 956.81 billion by 2025.
What’s fueling this growth? Clear consumer behavior. A recent survey showed that 76% of online buyers would rather make purchases in their own language, drawing a straight line between language and revenue.
For a service desk, these costs show up in a few painful ways:
- Sky-High Agent Overhead: Hiring multilingual agents is expensive and a nightmare to scale. You might hire three agents to cover Spanish in one time zone, only to realize you need another three for a new region.
- Crippling Inefficiency: When your team is wasting time on manual translation, they’re handling fewer tickets. This operational drag slows down your entire support organization.
- Brand Damage: Slow, clunky, and inconsistent support is a fast way to tarnish your brand’s reputation in new markets. It makes acquiring and, more importantly, keeping customers that much harder.
This is why an integrated, AI-powered translator isn’t just a cool tool—it’s a strategic weapon. It lets you centralize your best talent and empower them to deliver a consistently high-quality support experience to every single customer, no matter where they are or what language they speak.
Getting Your Jira Instance Ready for Seamless Translation

Any successful rollout, whether it’s a simple app or a major system overhaul, starts with a solid foundation. Before you even think about installing a multi language translator app, a little prep work can save you from a world of configuration headaches down the line.
Think of it as a pre-flight checklist. This isn’t just about clicking “install.” It’s about making sure you have the right permissions, confirming your plan’s compatibility, and getting the connections sorted for the AI engine that will be the powerhouse behind your global support desk. Getting these details right from the start is the difference between a smooth launch and a frustrating afternoon of troubleshooting.
Confirming Administrative Access and Project Permissions
First things first: you need the right keys to the kingdom. To install and configure an app from the Atlassian Marketplace, you absolutely must have Jira Administrator or Organization Administrator permissions. This is non-negotiable, as it’s what allows you to manage app settings, subscriptions, and integrations.
If you don’t have this level of access, you’ll hit a wall before you even start. The best move is to coordinate with your IT department or whoever manages your Atlassian suite ahead of time. A quick check now saves a ton of back-and-forth later.
Once your own access is confirmed, take a look at the permissions within the Jira Service Management projects you want to translate. The app will need to read and write comments to do its job. A quick scan of the project’s permission scheme will ensure the app’s user has the access it needs to translate tickets without a hitch.
Securing Your Translation Engine API Key
The magic behind any AI translation app is its connection to a powerful engine like Google Translate or DeepL. These services do the heavy lifting of language conversion. To link your Jira instance to one of them, you need an API key.
An API key is basically a unique password that authenticates requests from your Jira to the translation service. It’s critical to treat this key with care—store it securely and never, ever expose it publicly.
Getting a key is pretty straightforward:
- Pick Your Provider: Decide if you’ll use Google Cloud Translation, DeepL, or another supported service. This often comes down to pricing, specific language support, or existing company accounts.
- Set Up a Project: In your provider’s console (like the Google Cloud Platform), you’ll usually need to create a new project just for this integration.
- Enable the API: Within your new project, find and enable the specific translation API service.
- Generate the Key: Follow the steps to create your new API key. Make sure to copy and paste it somewhere safe, as you’ll need it during the app setup.
For a more detailed walkthrough, our article on using Google Translate for Jira and JSM breaks down this exact process.
Pro Tip: When you create your API key, do yourself a favor and set up usage quotas or budget alerts in the provider’s dashboard. This is a fantastic safety net to prevent any surprise bills if your ticket volume suddenly spikes.
Before you jump into the installation, running through a quick checklist can ensure everything is in place. It’s a simple step that helps guarantee a smooth and predictable setup process.
Pre-Installation Checklist for Issue Translation for JSM
Check Item | Why It’s Important | Quick Action |
---|---|---|
Admin Permissions | Required to install and configure apps from the Atlassian Marketplace. | Verify you have Jira Administrator or Organization Administrator rights. |
Project Permissions | The app needs to read and write comments in the target JSM projects. | Review the Permission Schemes of the relevant projects. |
Translation API Key | Authenticates the connection between Jira and the translation engine (e.g., Google, DeepL). | Generate and securely store the API key from your chosen provider. |
Jira Plan Compatibility | Ensures your Jira Cloud plan (Standard, Premium, Enterprise) supports all app features. | Check the app’s Atlassian Marketplace page for compatibility details. |
Taking a few minutes to tick these boxes will make the actual installation and configuration feel like a breeze.
Verifying Jira Plan and App Compatibility
Finally, a quick compatibility check is always a smart move. Most modern apps on the Atlassian Marketplace, including Issue Translation for JSM, are built for Jira Cloud. It’s good practice to confirm that your specific Jira plan—whether it’s Standard, Premium, or Enterprise—fully supports all the app’s features.
You can find this information right on the app’s Marketplace page, which lists hosting compatibility and any plan-specific requirements. This tiny step ensures you won’t run into any subscription-level surprises after you’ve already started the process. By taking these few preparatory steps seriously, you’re setting the stage for a powerful and efficient multilingual support system.
Installing and Configuring Your First Translator App

Alright, you’ve done the prep work and your Jira instance is ready to go. Now for the fun part: bringing your multi language translator to life. Don’t worry, this isn’t some dense technical manual. We’re going to walk through installing the ‘Issue Translation for JSM’ app right from the Atlassian Marketplace and get it configured for immediate impact.
We’ll go from finding the app to making those first critical setup choices. These initial settings are more than just clicking buttons; they’re the foundation for a seamless, global customer experience.
Finding and Installing the Right App
First things first, head over to the Atlassian Marketplace. If you’re not familiar, think of it as the app store for all things Atlassian.
In the search bar, type in “Issue Translation for JSM.” This will take you directly to the app listing page, where you can see details from the provider (Resolution GmbH), check out user reviews, and find pricing info.
From here, the installation is refreshingly straightforward.
- Hit “Try it free.” This will kick off a 30-day free trial, which is more than enough time to put the app through its paces and see the value it delivers.
- Pick your Jira site. If you’re managing multiple Jira instances, just make sure you select the correct one from the dropdown.
- Click “Start free trial.” Atlassian takes over from here, automatically adding the app to your Jira instance in the background.
The whole process usually takes just a couple of minutes. You’ll get a confirmation message once it’s done, and the app will be ready for you under Jira’s “Manage apps” section.
Your Initial Configuration Journey
With the app installed, it’s time to plug in that translation engine API key you prepared earlier. This is the moment you connect Jira to the powerful AI that will be doing all the heavy lifting.
Navigate to the app’s configuration page inside your Jira settings. Here, you’ll find a field to input the API key from your chosen provider, whether that’s Google Translate or DeepL. This connection is the engine for every single translation, so getting it right is crucial.
After you’ve pasted in your API key, you’ll want to make sure everything is talking correctly. Most good apps have a simple “Test Connection” button. Click it. The app will send a quick ping to the translation service and confirm it’s working. A success message means you’re officially in business.
“Your initial setup choices are the blueprint for your entire multilingual support workflow. Defining a default language and selecting your supported languages from the start creates a predictable and efficient environment for your agents and customers.”
Setting Project-Specific Translation Rules
One of the most powerful features you’ll configure right away is setting translation rules on a per-project basis. This is a game-changer because not every service desk has the same linguistic needs. Your internal IT help desk might be 99% English, but your customer-facing product support portal needs to handle a dozen different languages.
Here’s how you can tailor the settings for a specific JSM project:
- Set a Default Language: This is your support team’s native tongue (e.g., English). The app will use this as the target language for all incoming customer messages.
- Define Supported Languages: Hand-pick the languages you want the app to translate. You can choose from an extensive list, covering everything from Spanish and German to Japanese and Mandarin.
- Choose a Translation Mode: Decide how your agents will see the translations. Bilingual mode displays both the original text and the translated version side-by-side, which is fantastic for context and transparency. Invisible mode, on the other hand, just shows the translated text for a cleaner, more conversational feel.
This level of granular control means the multi language translator fits your organization’s structure, not the other way around. You can start with a single project to test the waters and then roll it out as your global support needs grow. We dive deeper into what’s possible in our overview of Issue Translation for Jira.
The Growing Need for Integrated Solutions
The demand for tools like this is exploding. The language services industry is expanding at a breakneck pace as businesses connect with global audiences. In 2025, the market was valued at an impressive USD 78.83 billion. Forecasts show it skyrocketing to USD 144.19 billion by 2032, a clear sign that seamless, cross-language communication is no longer optional.
This growth is precisely why integrating a translator directly into a core system like Jira isn’t just a nice-to-have—it’s a competitive necessity in today’s global market.
Automating Your Workflows for Multilingual Support Teams
So, you’ve got your multi language translator installed and configured. That’s a huge first step in bridging communication gaps. But the real game-changer is moving beyond one-off manual translations and building smart, automated workflows. This is how you level up your Jira Service Management instance from a reactive ticketing tool into a proactive, self-managing engine for global support.
The end goal? To get rid of manual clicks and copy-pasting for good. Think about it: a world where incoming customer requests and your agent’s replies are translated instantly, without anyone lifting a finger. This isn’t just about shaving a few seconds off each ticket. It’s about building a completely seamless experience that slashes resolution times and lets your team focus on what they’re paid to do: solve complex problems.
Setting Up Automatic Translation Triggers
The heart of all this automation is triggers. With Issue Translation for JSM, you can set up automatic translations for both incoming messages from customers and the replies your agents send out.
This means the moment a customer in Japan submits a ticket, it lands in your agent’s queue in perfect English. When your agent types a response in English, the customer sees it in flawless Japanese. It all happens in the background, powered by sophisticated language detection.
Here’s a simple look at how that flow works.

This visual breaks down the process: raw text comes in, gets processed, and comes out as actionable, translated content—no human intervention required.
To switch this on, just head into the app’s settings inside your Jira project. You’ll see toggles to enable automatic translation for:
- Customer Comments: Instantly translate any new message a customer submits through the JSM portal.
- Agent Comments: Automatically translate your team’s public or internal comments into the customer’s language.
Flipping these switches is your first move toward a truly “hands-off” multilingual workflow, making life easier for everyone.
Creating a Smart Triage Workflow
Let’s put this into a real-world context. One of the biggest headaches for any support team is just getting tickets to the right agent or queue. Using a multi language translator, you can automate routing based on the customer’s language.
Imagine your company is seeing a surge of new customers from Latin America and Germany. You can build a “triage” workflow that automatically spots tickets in Spanish or German, translates them, and routes them to the right place.
Here’s a quick blueprint for building it:
- Leverage the ‘Customer Language’ Field: The Issue Translation app conveniently adds a custom field to your tickets that logs the detected language from the customer’s very first message.
- Build Automation Rules: Jump into Jira’s native automation settings. You can create a rule that uses this language field as a trigger. For example:
WHEN
a new ticket is createdAND
‘Customer Language’ is ‘Spanish’THEN
translate the issue descriptionAND
assign it to the ‘Spanish Triage’ queue. - Set Up Language-Specific Queues: Create dedicated queues in your JSM project using JQL to filter tickets by this language field. This gives your team a clean, organized view of all incoming requests from different regions.
This simple bit of automation ensures that important tickets from key markets get immediate attention, without anyone having to manually sift through a crowded inbox. For more ideas on improving the customer journey, check out our guide on delivering exceptional multilingual customer service.
A well-designed automated workflow does more than just translate text; it directs the right conversations to the right people at the right time. This proactive approach is the hallmark of a truly efficient global support operation.
Manual vs. Automated Translation Triggers
While full automation is incredibly powerful, there will always be situations that call for a human touch. Knowing when to automate and when to step in manually is key to building a flexible, efficient system.
I’ve seen teams struggle with this, so here’s a quick comparison to help you decide which approach fits best for different scenarios.
Manual vs. Automated Translation Triggers
Scenario | Recommended Approach | Key Benefit |
---|---|---|
High-Volume, Standard Inquiries | Fully Automated | Maximizes efficiency and guarantees fast response times for common, everyday issues. |
Sensitive or Complex Legal Issues | Manual Translation with Review | Gives agents the chance to review and tweak AI translations for critical nuance and accuracy before hitting send. |
Escalated Technical Problems | Automated with Bilingual View | Provides agents with the original text for crucial context while still speeding up the conversation. |
Internal Team Collaboration | Fully Automated | Breaks down language barriers between globally distributed team members working on the same ticket. |
In the end, the best strategy is usually a hybrid one. Set most of your customer interactions to translate automatically, but empower your agents to manually trigger, view, or edit translations for those tricky edge cases that need a careful eye. This gives you the best of both worlds: the raw speed of automation paired with the precision of human oversight. Your multi language translator becomes an adaptable tool that truly fits how your team works.
Adopting Best Practices for Long-Term Success
Getting a powerful tool up and running is one thing. Turning it into a strategic asset that pays dividends for years to come? That’s a whole different ballgame. Simply installing a multi language translator isn’t the finish line; it’s the starting pistol for building a smarter global support operation.
This is about moving beyond the initial setup. We’re talking about empowering your team, fine-tuning the tool’s performance, and keeping a sharp eye on the results. These are the pro tips that will elevate your service desk from just having a translation feature to running a truly scalable, effective, and lasting global support powerhouse.
Train Agents to Trust and Use AI Translations
Let’s be honest, one of the first hurdles you’ll likely hit is agent adoption. Some of your team might be skeptical of AI-generated text, worrying it’ll sound robotic or, worse, misrepresent what a customer is saying. You’ve got to tackle this head-on.
Show them the ropes. Walk them through features like the bilingual view, which provides the full context by displaying both the original message and the translation side-by-side. Encourage them to use the built-in editor for small tweaks. This simple act builds immense confidence and ensures your company’s unique voice is never lost in translation. This isn’t about replacing their expertise; it’s about amplifying it.
By training your team to see the AI as a reliable co-pilot, you’re not just translating tickets. You’re turning your best problem-solvers into global communicators who can tackle complex issues in any language.
Create a Shared Glossary for Company Jargon
Every company has its own dialect—product names, internal project codenames, technical acronyms. A standard translation engine has no idea that “Project Phoenix” is your new software release. This is where a shared glossary becomes your secret weapon for accuracy.
Get your team involved and compile a list of all your company-specific terms and their official translations. Most enterprise-grade translation services, like the ones used by Issue Translation for JSM, let you upload this custom glossary. It’s a simple step that provides the AI with critical context, guaranteeing your unique terms are translated consistently and correctly, every single time. For technical support teams where precision is everything, this is non-negotiable.
Set Up a Customer Feedback Loop
No AI is perfect. Once in a while, a translation might just miss the mark. Don’t see this as a failure—see it as a free lesson in getting better.
Create a simple way for customers to flag translation issues. It could be as easy as adding a line to your email signature: “See a translation that looks off? Let us know!” When that feedback rolls in, you can use it to update your glossary or report the issue to the translation service provider. This creates a powerful cycle of continuous improvement, making your multi language translator smarter with every ticket. Plus, it shows customers you’re serious about clear communication and value their experience.
Monitor API Usage to Manage Costs
Finally, don’t let costs sneak up on you. Keep a firm handle on your spending by actively monitoring your translation API usage. Providers like Google Cloud or DeepL offer dashboards that give you a crystal-clear view of your consumption. Make checking this part of your monthly routine.
This habit helps you spot trends, like which languages are busiest, and allows you to forecast your budget with confidence. Many services also let you set spending limits or alerts, which is a lifesaver for preventing surprise bills.
Staying on top of this data ensures your multilingual strategy is not only effective but also financially sound. The machine translation technology segment, valued at USD 650 million in 2020 and projected to hit USD 3 billion by 2027, isn’t slowing down. Managing these powerful services well is just smart business, especially after the pandemic drove a 40% increase in demand. You can learn more about these fascinating translation statistics.
Even with a solid plan, you probably still have some practical questions about how a multi-language translator actually works for your team day-to-day. Let’s dig into some of the most common things we get asked, from performance to the real costs involved. Getting these cleared up will help you move forward with confidence.
Will an AI Translator Replace My Support Agents?
Not a chance. In fact, it’s just the opposite. This is a big misconception we hear all the time.
Think of an AI translator as a force multiplier for your best people, not a replacement. It takes your most skilled agents and gives them the power to handle requests from anywhere in the world. Language barriers disappear, letting them focus purely on solving the problem at hand.
What this really does is let you centralize your top talent. Instead of scrambling to hire separate agents for every single language, you can build one elite team that delivers top-notch support to every customer, no matter what language they speak. It just makes your entire support operation more efficient and way easier to scale.
How Accurate Is AI for Technical Support?
Today’s AI translation engines, like DeepL and Google Translate, are impressively accurate. They’re especially good with the kind of specific, structured language you see all the time in technical support.
Of course, no machine translation is ever going to be 100% perfect. But for troubleshooting complex issues, they are more than capable of making communication clear and effective.
Here’s a pro tip: to get even better results, set up a glossary for your company’s unique jargon, product names, or acronyms. This simple step trains the AI to understand your business, dramatically cutting down on misunderstandings and keeping your terminology consistent across every language.
A well-configured AI translator does more than just swap out words; it learns your business’s unique vocabulary. This customization is the key to maintaining precision in technical conversations and building trust with your customers.
What Are the Real Costs Involved?
Alright, let’s talk money. Understanding the financial side of things is obviously a huge piece of the puzzle. When you implement a solution like Issue Translation for JSM, you’re typically looking at two main costs:
- The Jira App Subscription: This is your predictable, fixed cost. It’s usually a monthly or annual fee based on how many users you have.
- Translation API Usage: This is the variable part, coming from whichever engine you choose (like Google Cloud Translation). The cost is based on how much you translate—specifically, the number of characters your team processes.
But here’s the good news: the API cost is often a lot lower than people think. Many providers have a pretty generous free tier that can cover millions of characters a month. For many small to medium-sized teams, this means the cost ends up being minimal, or even zero.
This makes adding a powerful multi-language translator to your workflow incredibly cost-effective. If you want to dive deeper into the business case, check out our report on automatic translation benefits. It really breaks down how this technology delivers a strong return on investment by cutting overhead and making your team more efficient.
Ready to break down the language barriers in your Jira Service Management instance? With resolution Reichert Network Solutions GmbH, you can give your team the tools they need to deliver truly exceptional global support.
Try Issue Translation for JSM free on the Atlassian Marketplace and start your trial today.