But having this information available doesn’t necessarily mean Confluence employee training is effective for everyone.

For L&D and Training Managers, the challenge often isn’t creating more content. It’s turning existing knowledge into structured employee training that people can follow, complete, and understand.

The good news? If your organization already uses Confluence, you can leverage Confluence employee training instead of starting from scratch.

Why Confluence employee training needs more than a knowledge base

A Confluence knowledge base is designed to make information accessible. Employees can search for answers, explore documentation, and collaborate on shared knowledge.

Training, however, requires a different approach.

Imagine a new employee joining your company. You share five Confluence pages, a product demonstration, two internal policies, and a few videos.

Everything they need is technically there. But:

• Where should they start?
• Which materials should they complete first?
• How can you confirm they’ve reviewed the required content?
• How do you know whether they understood it?
• How can you monitor their progress?

This is where knowledge management and learning management differ.

A knowledge base helps employees find information when they need it. A learning program guides employees through specific content to achieve defined learning objectives.

For L&D teams, the opportunity is to connect both. The six steps below answer each of these questions, using the content you already have.

Step 1: Identify existing Confluence content for employee training

Before creating new training materials, review what’s already available.

Start with content that employees frequently need during onboarding, role-specific training, or ongoing professional development. For example:

The objective is to identify existing, maintained resources that can become part of a learning experience.

Step 2: Organize your content into a learning structure

Once you’ve selected your materials, organize them into a clear learning sequence.

Rather than sharing a collection of unrelated links, group content into logical topics. For example, a new employee training course could include:

1. Section 1: Welcome to the company
   • Company introduction
   • Mission, values, and team structure
2. Section 2: How we work
   • Internal communication guidelines
   • Tools and workflows
   • Employee policies
3. Section 3: Your role
   • Team-specific procedures
   • Product or service documentation
   • Knowledge assessment

Alternatively, you can organize the same content into separate courses and bring them together in a Learning Path.

For example, a New Employee Onboarding Learning Path could include:

1. Course 1: Welcome to the Company
   • Company introduction
   • Mission, values, and team structure
2. Course 2: How We Work
   • Internal communication guidelines
   • Tools and workflows
   • Employee policies
3. Course 3: Your Role
   • Team-specific procedures
   • Product or service documentation
   • Knowledge assessment

This structure gives learners a clear starting point and helps them understand what comes next.

With Smart Courses for Confluence, you can organize content into courses, sections, and individual learning components. You can include existing Confluence pages alongside videos, documents, text, and quizzes, instead of rebuilding your entire knowledge base inside a separate training platform. Your pages stay in Confluence, where your teams already maintain them.

To ensure learners review important content, you can set a minimum reading time on a component so they can’t skip ahead in seconds.

Step 3: Create learning paths

Not every learning objective can be covered in a single course.

New hires might need company orientation, security awareness, product knowledge, and role-specific training. Experienced employees might need advanced product training or periodic refresher courses.

This is where Learning Paths become useful. Instead of assigning each course separately, you can create a learning journey that brings related courses together. For example, a new employee Learning Path could include:

1. Company introduction
2. Internal tools and processes
3. Security awareness
4. Product knowledge
5. Role-specific training

Smart Courses supports Learning Paths that combine multiple courses and exams, with optional linear progression.

This allows training managers to guide employees through the right material in an appropriate order, without requiring them to figure out what to learn next.

Step 4: Assign training to the right employees

Making training available is one thing. Ensuring the right employees receive it is another.

Some courses may be relevant to everyone, while others are required only for specific teams.

With Smart Courses, training managers can assign courses to individual users or groups, set due dates, add a message, and send reminders. For example:

• HR assigns onboarding training to new hires.
• IT assigns security awareness courses to relevant employees.
• Support managers assign product knowledge training to support teams.
• Department leads assign updated process training to their teams.

For recurring needs like onboarding, continuous assignments keep training assigned as your teams change, so new team members get the right courses without a manager setting it up each time.

This makes the training process easier to coordinate, especially as teams grow and training requirements become more diverse.

Step 5: Check understanding with quizzes and assessments

Opening a document doesn’t necessarily mean someone understood it.

For L&D teams, assessments help determine whether learners have understood important information and can apply what they’ve learned.
Smart Courses supports seven question types: single choice, multiple choices, freetext, matching, ordering, fill in the blank, and essay. This lets you test recall, reasoning, and written understanding within the same course.

For example, after completing a product knowledge section, employees could answer questions about common features, customer use cases, or troubleshooting procedures.
In exam mode, you can set a minimum pass score, limit the number of exam attempts, choose whether learners see their results, and issue certificates when learners meet the required completion criteria.

This connects training content with measurable learning outcomes rather than relying entirely on page views or self-reported completion.

Step 6: Track employee training progress

Once training is assigned, managers need visibility into participation and completion.

Without dedicated learning management functionality, this often involves manually following up with employees or maintaining separate tracking spreadsheets.

Smart Courses provides Insights dashboards that help training managers monitor learning activity and results. Depending on the dashboard, managers can review course completion, learner status, assessment results, and related training data. They can also export reports for further analysis.

This helps answer questions such as:

• Who has completed their assigned training?
• Which learners are still in progress?
• Who has overdue assignments?
• Which courses may require attention?

Instead of chasing updates across different channels, L&D teams have a clearer view of training progress.

How Atlassian’s Teamwork Collection fits into employee training

Structured learning works best when it stays connected to the knowledge and daily workflows employees already use.

Atlassian’s Teamwork Collection brings together Confluence, Jira, Loom, and Rovo to connect documentation, work, video communication, and knowledge discovery. Each can support a different part of employee learning:

• Confluence: Maintain the documentation, policies, and resources employees need to learn.
• Loom: Record walkthroughs and explanations that make complex procedures easier to follow.
• Jira: Connect learning-related tasks and follow-up activities to everyday workflows.
• Rovo: Help employees discover relevant knowledge and find answers across connected resources.

Smart Courses adds a dedicated learning layer within Confluence, letting organizations organize content into training programs, assign learning, assess understanding, and track progress.

Smart Courses runs inside Confluence, so your training is built directly on your Confluence content. Jira, Loom, and Rovo complement Smart Courses: they don’t integrate directly, but they strengthen the environment where you create, find, and put your training content into practice.

From knowledge sharing to employee learning

Your Confluence knowledge base is already an investment in your organization’s knowledge. Turning that information into structured training helps you get more value from it.

You can start with a single course, such as employee onboarding or product knowledge training, using content your team has already created. Then, as your learning needs grow, you can add assessments, assignments, Learning Paths, and progress tracking.

You don’t need to recreate your knowledge. You need a better way to help employees learn from it.

With Smart Courses for Confluence, you can build a learning experience around the knowledge your organization already maintains.

Try Smart Courses for Confluence on the Atlassian Marketplace or book a demo

FAQ

Can I use existing Confluence pages in a course?
Yes. Smart Courses lets you add existing Confluence pages to a course alongside videos, documents, text, and quizzes, so you don’t rebuild content in a separate platform.

What is the difference between a course and a Learning Path?
A course groups content into sections on one topic. A Learning Path combines several courses and exams into one journey, with optional linear progression.

What question types does Smart Courses support?
Seven: single choice, multiple choices, freetext, matching, ordering, fill in the blank, and essay.

Can I issue certificates in Confluence?
Yes. Smart Courses can issue certificates when learners meet the completion criteria, such as reaching the minimum pass score of an exam.

How do I track who completed their training?
Insights dashboards show course completion, learner status, and assessment results, and you can export reports for further analysis.

Can Confluence be used for employee training and learning management?
Yes. Confluence can serve as a central knowledge base for employee training. With Smart Courses for Confluence, you can turn existing documentation into structured courses, create Learning Paths, assign training to employees or groups, assess their understanding through quizzes and exams, issue certificates, and track learning progress through Insights dashboards.

That means all four Creativas apps are now developed on Atlassian’s cloud app platform:

• Smart Courses for Confluence: LMS, employee training, onboarding, quizzes and compliance
• Smart Terms: glossary and terminology management for Confluence and Jira
• Smart Tables for Confluence: table filtering, reporting, charts, formulas, calculations and SQL views
• Smart Images for Confluence: image editing, image maps, sliders and galleries

Getting here took years of work.

Moving established apps with real customers, data, workflows and years of functionality wasn’t simply about changing the technology underneath them. We had to rebuild some parts, redesign others, and work around limitations as Forge itself continued to evolve.

Now all four apps share the same Forge foundation.

And for us, that’s where the interesting part starts.

Why did we move our Atlassian apps to Forge?

Forge is now Atlassian’s preferred platform for building Cloud apps. Since September 17, 2025, only Forge apps can be submitted as new apps to the Atlassian Marketplace, and Atlassian says it’s delivering new extensibility features on Forge. Read Atlassian’s Forge documentation for Confluence.

Atlassian Connect is also approaching end of support on January 31, 2027.

So we couldn’t ignore moving to Forge.

But we didn’t want to treat it as a deadline or a box to check.

Forge is also where Atlassian is investing in capabilities that can shape the next generation of Cloud apps: AI, Rovo extensions, Forge LLMs, Teamwork Graph and deeper connections across the Atlassian platform.

We wanted our apps to be ready for that future.

What is Atlassian Forge?

Atlassian Forge is the development platform for building apps that extend Jira, Confluence and other Atlassian Cloud products.

With Forge, Atlassian manages core areas of the platform such as infrastructure, compute and hosted storage, while app developers build the functionality customers interact with. Forge is Atlassian’s preferred cloud app development platform.

For Creativas, that gives us a common foundation across our products while keeping our apps closer to the Atlassian ecosystem they are designed for.

What does moving to Forge mean for our customers?

The biggest change isn’t something customers need to learn.

It’s what Forge allows us to build behind the scenes.

• Closer alignment with Atlassian Cloud: Our apps can evolve alongside the platform they extend instead of depending on a legacy framework.
• Access to new Atlassian capabilities. Forge gives us more opportunities to work with capabilities such as Rovo Agents, Forge LLMs and Teamwork Graph.
• A stronger foundation for AI. Forge LLMs allow Forge apps to call Atlassian-hosted large language models, giving developers a platform-native way to build AI functionality.
• Atlassian-managed infrastructure. Forge provides Atlassian-managed infrastructure and hosted storage, including data residency support for persistent Forge-hosted storage. Learn about Forge data residency.
• One foundation across our portfolio. Smart Courses, Smart Terms, Smart Tables and Smart Images can now evolve on the same Atlassian development platform rather than following separate technical paths.

And some of those benefits are already visible in the products.

Smart Courses: Building a Confluence LMS on Forge

Smart Courses for Confluence was the final piece of our Forge journey.

Smart Courses turns Confluence into a learning management system where teams can create and deliver employee training, onboarding programs, compliance courses, quizzes, exams, certifications and SCORM-based learning experiences.

Rebuilding an app with that much functionality on Forge required far more than moving a few components.

Courses, assignments, learner data, Insights and the workflows customers already rely on had to remain part of the experience while the app moved to its new foundation.

That work is now complete.

Smart Courses is on Forge, and that also gives us a better foundation for the next capabilities we want to bring into learning in Confluence, including more AI-assisted experiences and deeper connections with the Atlassian platform.

For teams looking for a Confluence LMS, employee training in Confluence, Confluence onboarding, or compliance training with SCORM, the technology underneath Smart Courses is now ready for where Atlassian Cloud is going next.

Smart Terms: A Forge-powered glossary for Confluence and Jira

With Smart Terms, teams can build and manage an enterprise glossary, define terminology, connect related vocabulary and automatically highlight terms across Confluence and Jira content.

Forge has already started changing what we can add to that experience.

We launched Lexi, our AI Glossary Assistant, to help teams analyze their Confluence knowledge, identify relevant terminology and create glossary content faster.

We’re also using Atlassian Forge LLMs for AI-assisted term translations, bringing AI into the terminology workflow using Atlassian-hosted models.

For organizations managing acronyms, technical terminology, product language or company-specific vocabulary, Smart Terms provides a Confluence glossary and terminology layer directly inside the Atlassian workspace.

And this is a good example of why our Forge migration matters: the benefit isn’t the migration itself. It’s what we can build because of it.

Smart Tables: Table filtering, reporting and AI queries in Confluence

Confluence tables often start simple. Then the data grows.

Teams need advanced filters, calculations, charts, pivot tables, grouping, reporting and different ways to understand the same data.

That’s where Smart Tables for Confluence comes in.

Smart Tables extends native Confluence tables with table filtering, charts, pivots, Excel-like calculations and additional reporting capabilities. Its SQL Views also let teams query their table data and create more specific views without duplicating the source table.

Forge is also opening new ways to simplify those workflows.

With AI Query, users can describe the result they need and generate the SQL query instead of having to write it manually.

For someone searching for a Confluence table filter, Confluence reporting app, pivot tables for Confluence, or SQL queries in Confluence, Smart Tables now combines those established capabilities with a Forge foundation we can continue building on.

Smart Images: Image editing and visual content inside Confluence

Not every Forge benefit needs to involve AI.

Smart Images for Confluence is our visual toolkit for teams that want to do more with images without constantly moving between Confluence and external editing tools.

Teams can edit and annotate images, create interactive image maps, and display visual content through sliders and galleries directly in Confluence.

Smart Images is also fully Forge-developed, giving it the same foundation as the rest of our Cloud portfolio.

For teams searching for a Confluence image editor, image map for Confluence, Confluence image gallery, or image slider, those workflows can stay where the documentation itself lives.

Forge, security and trust

Security was also an important part of why moving toward Forge made sense for us.

Forge provides Atlassian-managed infrastructure alongside built-in platform security controls. Atlassian documents security for Forge through a shared responsibility model, where Atlassian manages parts of the underlying platform while Marketplace Partners remain responsible for the security decisions and functionality within their apps. Read Atlassian’s Forge security guidance and shared responsibility model.

That doesn’t mean Forge removes our responsibility as a Marketplace Partner.

It means we’re building on an infrastructure designed specifically for Atlassian Cloud apps while continuing to take responsibility for how our apps are built, maintained and secured.

Forge also provides data residency support for persistent Forge-hosted storage.

For qualifying Forge apps, Atlassian also offers Runs on Atlassian, a trust designation with requirements around Atlassian-hosted compute and storage, data residency and external data egress controls.

Today, Smart Terms, Smart Tables and Smart Images carry the Runs on Atlassian badge on the Atlassian Marketplace.

All four apps are Forge-developed; Runs on Atlassian is a separate eligibility and trust designation.

Forge isn’t the finish line

Over the last few years, we did a lot of behind-the-scenes work to get our portfolio here.

There were limitations to work around, functionality to rebuild, architecture to rethink, and a platform that was evolving while we were building on it.

But the objective was never simply to say: “Our apps are on Forge.”

The objective was to make sure Smart Courses, Smart Terms, Smart Tables and Smart Images are ready for what comes next.

We’re already seeing that with Lexi, Forge LLM-powered translations and AI-generated SQL queries.

Next, we’ll continue looking at where capabilities such as AI, Rovo, Teamwork Graph and other Forge improvements can solve real problems across our apps.

Not because every feature needs AI, not because every new Atlassian capability needs to become a feature. But because when something can genuinely make training easier, terminology clearer, data easier to understand or Confluence content better to work with, our apps are now in the right place to build it.

Filtering, sorting, grouping, and pivot tables can handle a lot. But when you need more specific views, combined conditions, or custom summaries, SQL gives you another way to work with the same data.

With Smart Tables for Confluence, you can convert your native Confluence tables into Smart Tables and create SQL Views directly from them. And if you don’t know SQL, AI Mode can generate the query for you.

Let’s see how it works.

Can you use SQL with a native Confluence table?

Not directly.

Native Confluence tables are great for organizing information, documenting processes, or keeping lightweight trackers inside a page.

But a native table doesn’t provide an SQL editor where you can run something like:

SELECT Task, Team, Owner, Priority, Status, Due Date
FROM T1
WHERE Priority = 'High'
AND Status = 'Open'
AND Due Date <= CURRENT_DATE + INTERVAL 14 DAY
ORDER BY Due Date ASC;

Smart Tables adds that layer.

Instead of rebuilding the data elsewhere, you can convert your existing native Confluence table into a Smart Table and keep working with the information already on your page.

From there, you can use familiar Smart Tables features such as filters, sorting, grouping, formulas, pivot tables, and charts or create an SQL View when the question gets more specific.

So, let’s start from the beginning.

Step 1: Start with your Confluence table

Imagine you’re managing a project tracker in Confluence with columns such as:

• Task
• Team
• Owner
• Priority
• Status
• Due Date
• Budget

For normal day-to-day work, this table might be perfectly manageable. You can read through the rows, update statuses, and use Confluence as the shared place where the team keeps the latest information.

However, the problem arises when different people need different answers from the same SQL table. A Project Manager may want to see only open high-priority work. A team lead may want to know which team has the most open tasks. Finance may only care about budget totals. You could create separate tables for each need.

But now you have multiple versions of the same data to maintain. Instead, let’s keep one source table and query it.

Step 2: Convert your native Confluence table to a Smart Table

If your data is inserted inside a Smart Table macro, you can skip this step.

If you’re starting with a native Confluence table, you don’t need to recreate it manually.

Open the Smart Tables menu from the page header and select Convert to Smart Table.

The Table converter will show the tables available on the page. Select the one you want to convert and save your changes.

Your existing Confluence table is now a Smart Table, which means you can work with the same data while adding more advanced table features.

This is an important part of the workflow: you’re enhancing the table you already have rather than starting again somewhere else.

Step 3: Create your first SQL View

Now open your Smart Table from the Confluence page viewer.

From the + View menu, select SQL table. A new SQL table is created from your Smart Table data, and its edit mode opens automatically. One detail you’ll need to know before writing anything:

Your source Smart Table is referenced in SQL as:

So instead of querying the table by its page title or Smart Table name, your query uses FROM T1. Let’s try a simple example. Suppose we want to see every high-priority task that is still open:

Click Run Query. The result appears directly below the SQL editor.

Instead of changing the source Smart Table, you’ve created a focused view answering one particular question. As the source data changes, the SQL table stays connected.

Step 4: Understand what the query is actually doing

If you’re not very familiar with SQL, the query above can look more intimidating than it really is.
SELECT decides which columns you want to see. FROM T1 tells Smart Tables which source data you’re querying. WHERE defines the conditions the rows must meet. AND lets you combine more than one condition. ORDER BY decides how the final results should be arranged.

So this:

WHERE `Priority` = 'High'
AND `Status` = 'Open'

simply means:

Only show rows where the task is both high priority and open.

That’s where SQL becomes particularly useful. Instead of manually combining several filters every time you need an answer, you can define the exact conditions in one query and keep the result as its own view.

One more thing to remember: Smart Tables references column names using backticks in SQL queries.

For example:

`Due Date`

or:

`Daily Budget ($)`

Step 5: Go beyond filtering and summarize your Confluence table

SQL isn’t only another way to filter rows.

You can also use it to summarize the information inside your Smart Table.

Let’s say you want to know how many high-priority open tasks each team currently has.

Instead of returning every individual task, you can ask SQL to count them:

Now your detailed project tracker becomes a simple summary showing the number of open, high-priority tasks per team.

You can use the same approach to answer other questions, such as identifying which team has the most tasks assigned or comparing workloads across teams.

For example, to count the total number of tasks assigned to each team:

This gives you a breakdown of tasks by team, ordered from the highest to the lowest.

Your original Smart Table remains unchanged. You’re simply creating another view of the same data.

Step 6: Don’t know SQL? Use AI Mode

This is the part that makes SQL Views useful beyond technical teams. You don’t necessarily need to write the query yourself. From the SQL table toolbar, switch from SQL to AI Mode. Instead of writing code, describe the result you’re looking for in plain language. For example:

“Count all open high-priority tasks by team and show the teams with the highest number first.”

Run the request. Smart Tables generates the SQL query based on your table and your instructions. The SQL editor then opens automatically so you can see both the generated query and its result. That means AI Mode doesn’t completely hide the SQL. You can review what was generated, use it as-is, or adjust it if needed. It can also be a good way to learn.

Ask for something in plain language, review the SQL it produces, change the request, and see how the query changes.
If you don’t see AI Mode, the AI Engine is controlled from Confluence administration → Apps → Smart Tables configuration. A Confluence administrator can manage the setting from there.
And as with any AI-generated output, review the query and its results before relying on it for important reporting.

Step 7: Create different views without creating different source tables

Your main Smart Table can remain the source of truth while different SQL Views answer different questions.

Instead of duplicating the source table for every reporting need, create multiple SQL Views from the same underlying data. When the source data changes, those views stay connected.

And because SQL is another Smart Tables view type, it can sit alongside your Table, Pivot Table, and Chart views instead of moving reporting into another tool.

A few details that will save you time

Create and edit SQL tables from the page viewer: SQL tables are created from the Confluence page viewer, and inline editing lets you adjust your SQL View directly without going back to the regular Confluence page editor.

Use T1 for your source data: If your query can’t find the table, make sure you’re referencing the Smart Table as T1.

Check AI Engine settings if AI Mode is missing: The setting is managed by a Confluence administrator under the Smart Tables configuration.

Review AI-generated queries: AI Mode helps you create a starting point quickly, but your wording and table structure affect what it generates.

Save your Smart Table changes: When you’re finished creating or adjusting the SQL table, use the Smart Table Save button so the changes are stored for page viewers.

There is also one behavior worth remembering when duplicating content: SQL tables aren’t copied automatically when a Confluence page is copied, so they need to be added again on the copied page.

From a Confluence table to an answer

A table doesn’t become less useful as it grows.

Usually, people just start asking more complicated questions.

Native Confluence tables give teams a simple place to structure and share information. Smart Tables add more ways to work with that information through filters, formulas, grouping, pivot tables, charts, and now SQL.

When a normal filter answers the question, use the filter.

When you need to combine conditions, calculate totals, group results, or build reusable reporting views from the same source data, create an SQL View.

And when you know the question but not the SQL, describe what you need in AI Mode and let Smart Tables create the first query for you.

Confluence provides a central place for HR policy documentation, while Marketplace apps can add approval workflows, terminology management, and employee training.

Effective policy management goes beyond storing documents. It creates a clear process for keeping policies accurate, approved, accessible, understood, and up to date.

What is policy management in Confluence?

Policy management in Confluence is the process of creating, organizing, reviewing, approving, publishing, and maintaining company policies in one central environment.

An HR policy hub might contain an employee handbook, code of conduct, remote work and leave policies, security and data protection policies, benefits documentation, expense policies, and compliance procedures.

The difference between simply storing policies and managing them is control. HR teams should be able to identify a policy’s current version, owner, approver, and review schedule.

A clear process turns a collection of Confluence pages into a reliable policy management system.

Why HR policies become difficult to manage

As organizations grow, policies can become scattered across different tools, outdated, or difficult to track. Employees may not know which version is current, while ownership, review dates, and approvals become harder to follow.

Without a clear process, policies can remain outdated or be approved without a reliable record. A structured policy management process helps keep them current, accountable, and easier to manage.

How to manage HR policies in Confluence

A scalable system does not need to be complicated. It needs a clear structure, visible ownership, and a repeatable lifecycle.

Create a central HR Policy Center

Start by giving employees one place for official policies.

Organize policies into clear categories such as Employee Policies, Security & Compliance, Benefits, and Training.

The goal is simple: employees should know where to find the latest approved information without searching across multiple spaces, files, or tools.

Use a consistent policy template

A standard structure makes policies easier to create and maintain.

Each policy can include essential information such as the policy owner, status, effective date, last review date, next review date, scope, responsibilities, and related documentation.

Using the same structure across policies also makes missing or outdated information easier to spot.

Assign clear ownership

Every important policy should have someone responsible for maintaining it.

Review frequency will vary by policy, but ownership should always be clear.

Define the policy lifecycle

Policies should not follow a simple:

Create → Publish → Forget

A more reliable process is:

This gives HR teams a repeatable process for managing policies throughout their lifecycle rather than reacting only when something becomes outdated.

Add approvals to your Confluence policy workflow

Some policies require formal review before they become official.

A data protection policy, for example, may need input from HR, Legal, IT, or senior management.

Confluence provides the documentation foundation, while Marketplace apps can add structured approval workflows, approval status tracking, decision history, and audit trails.

The process could look like this:

HR drafts the policy → Legal reviews it → Management approves it → The approved version is published → Employees access the current policy

This creates a clearer record of how a policy moved from draft to approved documentation and reduces uncertainty around which version employees should follow.

Make HR policies easier to understand

Making a policy available does not automatically make it easy to understand.

HR documentation often includes abbreviations, legal terminology, technical language, and company-specific concepts that may not be clear to every employee.

With Smart Terms for Confluence, HR teams can build a shared glossary directly inside Confluence and make definitions available in context as employees read policies.

A glossary could include terms such as PTO, PII, EAP, probation period, confidential information, or internal role classifications. Teams can also add related vocabulary, including acronyms, synonyms, and plurals, to keep terminology consistent across policies.

For organizations working across regions, Smart Terms supports multilingual glossaries, allowing teams to maintain terms and definitions in multiple languages.

Teams can also use Lexi, the Glossary AI assistant in Smart Terms, to scan Confluence content or uploaded documents and identify terminology worth defining. Lexi can draft definitions based on the surrounding content and translate suggested terms into enabled glossary languages.

Instead of asking employees to search elsewhere for an unfamiliar term, HR teams can add explanations directly in the policy while keeping one shared source for key company terminology.

Connect HR policies with employee training

Some policies need more than publication. Employees may need to understand the content, complete required training, and demonstrate that they know what is expected.

This is especially important for onboarding, information security, workplace conduct, data protection, and compliance.

With Smart Courses for Confluence, HR teams can turn policy documentation into structured learning without moving employees to a separate LMS.

For example, a new-hire learning path could combine courses on the Code of Conduct, Information Security, Data Protection, Remote Work, and Workplace Safety. Learning Paths can group related courses and exams into a defined training journey, while prerequisites and skills can control what employees need to complete or demonstrate before progressing.

HR teams can add quizzes and exams to check understanding, assign training with due dates, and issue certificates when required learning is completed. Course insights also help HR teams track progress and completion, rather than assuming that opening a policy means it was understood.

For recurring compliance requirements, courses can be scheduled to repeat so employees revisit required training when necessary.

The process becomes:

Policy published → Training assigned → Learning completed → Knowledge checked → Completion or certification tracked

By connecting policies with structured learning, HR teams can move beyond simply publishing information and create a clearer way to support onboarding, compliance, and ongoing employee training directly in Confluence.

Turn policy updates into employee learning

The connection between policies and training becomes especially important when a policy changes.

If your company updates its data protection policy, publishing the new version may not be enough. The change may also require approval, employee communication, updated training, and a knowledge check.

Update policy → Review and approve → Publish → Notify employees → Update training → Check understanding

This connects policy updates directly to employee learning instead of assuming employees will notice and understand a changed page.

The compliance content stays specialized. The learning experience lives in Confluence.

Try Smart Courses for Confluence free for 30 days.

Most organizations solve the first problem with specialized compliance courseware. But for teams already working in Confluence, training can still sit in a separate system from the policies, procedures, and documentation employees use every day.

Smart Courses lets you bring compatible, appropriately licensed BAI/ProSight compliance courseware into Confluence through SCORM, connecting specialized training with the workspace employees already use.

What is BAI compliance training?

BAI compliance training is now offered under the ProSight brand. BAI and the Risk Management Association (RMA) merged in 2024 to form ProSight Financial Association.

ProSight provides compliance courseware designed specifically for banks, credit unions, mortgage organizations, and other financial institutions.

Its training covers areas such as BSA and anti-money laundering, UDAAP, GLBA, cybersecurity, identity theft, lending regulations, deposit and transaction regulations, and corporate compliance.

Courses are built around financial-services roles and can include practical scenarios, interactive activities, and assessments. That specialized content is one reason organizations may prefer licensing established compliance training instead of recreating regulatory courses internally.

The challenge is not only the content

Good courseware solves the content problem. Employees still need an easy way to access and complete it.

For teams working across the Atlassian ecosystem, much of the supporting knowledge may already live in Confluence: internal policies, security procedures, risk-management documentation, department resources, and compliance guidance.

Putting training closer to that knowledge creates a clearer connection between the policy employees are expected to follow and the training they need to complete.

Instead of reading a policy in Confluence and then searching for the related course in another system, employees can access both from the same workspace.

Can BAI/ProSight courses run in another LMS?

Yes. ProSight licenses its programs for use in other learning management systems through its Content Provider Service, subject to the applicable agreement and approved LMS configuration.

Through its Content Provider Service, ProSight can provide licensed programs for use through a client’s approved learning management system.

An important distinction exists between ProSight/BAI-owned courseware and custom content your organization creates.

• ProSight/BAI courseware: You cannot assume you can freely export, copy, or reuse licensed ProSight/BAI training in another LMS. Whether you can deliver a course through an external LMS depends on your licensing agreement with ProSight and the delivery options they provide. Confirm the applicable permissions and SCORM availability with ProSight before requesting or importing course files.
• Custom content created by your organization: If you create and design your own training content within the platform, that content is separate from ProSight’s proprietary course catalog. Where the platform provides SCORM export for that custom content, you can export the resulting SCORM package and use it in a compatible LMS, subject to your organization’s rights to the content and the platform’s applicable terms.

In other words, licensed ProSight courseware and your own custom-created training should not be treated as having the same export rights.

Before planning the integration, confirm with ProSight that your agreement supports external-LMS delivery and that the course is available in a format compatible with SCORM 1.2 or SCORM 2004.

Once you have a compatible SCORM package that you are authorized to use in your LMS, Smart Courses can deliver it inside Confluence.

From ProSight courseware to training in Confluence

Start by selecting the ProSight courses that match your regulatory requirements and employee roles. Training for frontline employees, mortgage teams, managers, or compliance officers may differ, so match the right courseware to the right audience.

Once you select the courses, confirm with ProSight that your license and delivery arrangement support external-LMS use, and request the compatible course files or delivery method available for your account.

In Smart Courses, create a new course, enable the SCORM course option, open the course editor, and upload the compatible SCORM ZIP package you are authorized to use and have obtained through your ProSight licensing or delivery arrangement.

Smart Courses supports both SCORM 1.2 and SCORM 2004, so you can import compatible courseware without recreating the original training as Confluence pages.

Once published, you can assign the course to individual users or Confluence groups with a due date.

For recurring compliance requirements, group-based assignment can also help automate enrollment as employees join the relevant groups.

Administrators can then use Course Insights to follow learner progress, completion status, scores, and due dates.

Connect compliance training with your Confluence policies

This is where the combination becomes particularly useful.

Smart Courses provides a Course Card macro that can surface an individual published course on a Confluence page. The Course List macro can display a filtered collection of courses based on criteria such as categories, labels, or spaces.

Imagine an employee opening a Mandatory Banking Compliance Training page in Confluence.

At the top, the compliance team explains the program and provides links to internal policies. Below that, employees can find the relevant BSA/AML, cybersecurity, lending, identity-theft, or transaction-compliance courses available through Smart Courses.

The same page can also contain training deadlines, instructions, and contact information for the compliance team.

Employees move from policy → context → training without having to search across disconnected systems.

Who handles what?

A practical example

Consider a bank already managing its policies and procedures in Confluence.

The compliance team creates a Mandatory Banking Compliance Training page containing its internal compliance guidance and links to the policies employees are expected to understand.

Courses licensed from ProSight are imported into Smart Courses as SCORM packages and assigned by employee role.

Branch employees may receive BSA/AML and identity-theft training, while mortgage teams receive the lending-related courses relevant to their responsibilities.

Course cards and filtered course lists make that training accessible from the compliance area employees already use.

Meanwhile, the compliance team can use Insights to monitor who has completed the required training and where follow-up is still needed.

The result is a closer connection between what employees are expected to know and the training they are expected to complete.

What does Smart Courses track from SCORM?

Smart Courses captures the completion and score information sent by the SCORM package.

For SCORM 1.2, that includes lesson status and raw score. For SCORM 2004, Smart Courses uses completion status, success status, and raw score.

This allows learner results such as completed, incomplete, passed, or failed to appear in Smart Courses depending on the information provided by the package.

One limitation to keep in mind: Smart Courses does not currently capture individual question-level results from an imported SCORM course. It reports the package’s overall status and score.

Therefore, we recommend testing a new SCORM package before assigning it organization-wide to ensure its completion and scoring rules are reported as expected.

You can also enable certificates for SCORM courses when completion requirements are met.

Bring financial compliance training into Confluence

Compliance training works better when employees can easily find it alongside the policies and procedures it supports.

Once you have a compatible SCORM package that your ProSight licensing and delivery arrangement permits you to use in an LMS, upload it to Smart Courses, assign it to the right employees, and make it accessible from the Confluence pages your teams already use.

The compliance content stays specialized. The learning experience lives in Confluence.

Try Smart Courses for Confluence free for 30 days.

This is the reality for most growing teams, and it’s usually handled with a mix of onboarding docs, Slack messages, and a manager’s best guess about when someone is “ready.” That approach breaks down because knowledge and workload live in two systems that don’t talk to each other: a wiki page doesn’t know how loaded someone’s sprint is, and a sprint board has no idea whether they’ve finished security training yet.

Why do most onboarding programs fall short?

Three failure patterns show up again and again in growing teams:

• Readiness gets measured in time, not knowledge. Three weeks in is treated as a milestone regardless of whether someone has absorbed what they actually need to know.
• Training and delivery are treated as separate phases. Once someone touches their first ticket, onboarding is considered “done,” even if half the learning material is unfinished.
• Capacity is managed informally. “We’ll ease them in” rarely gets written down anywhere a manager or teammate can see it, so it doesn’t survive contact with a real sprint.

Fixing this doesn’t mean replacing Confluence or Jira; it means connecting the tools you already use so learning progress and workload planning inform each other in real time.

Structuring the Learning Path with Smart Courses for Confluence

The first half of a scalable onboarding system is making sure every new hire follows a consistent Learning path, not a scattered mix of pages and informal handovers.

With Smart Courses for Confluence, HR and team leads build a dedicated onboarding Learning Path that sequences everything a new hire needs into the right order: company policy, security training, product knowledge, engineering standards, and role-specific material. Learning Paths let you group multiple courses into a complete program, so a developer, a customer success manager, and a project manager can each follow a tailored track while still sharing common company-wide training.

A few things make this especially effective for onboarding at scale:

Courses can combine Confluence pages, PDFs, images, videos, and even HTML or SCORM packages so whatever format your documentation already lives in, it can become part of the learning journey without being rebuilt from scratch. Since Confluence pages stay connected, any updates your team makes are automatically reflected inside the course, so nobody is ever learning from an outdated version.

Assign courses directly, with due dates. Managers can assign individual courses to specific users or groups, complete with due dates and automatic notifications. This makes it easy to deliver mandatory training exactly when it’s needed: security training before a first login, product knowledge before someone joins their first customer call, instead of hoping people find it on their own.

Skills and quizzes turn learning into evidence. Interactive quizzes at the end of each chapter or course confirm a new hire actually understood the material, not just clicked through it. Combined with prerequisites and skills, onboarding becomes competency-based rather than time-based. Teams may require specific knowledge or a completed quiz to unlock the next stage, so nobody advances on assumption alone.

Insights give managers a real-time view. Built-in insights dashboards show course completion, quiz results, and overall learner progress across every new hire at once. Instead of chasing status updates in a 1:1, a manager can see exactly where each person stands and catch gaps before those gaps affect day-to-day work.

By turning existing Confluence knowledge into structured, trackable training, Smart Courses answers the first key onboarding question: what does this person actually know, and are they ready for the next step?

Managing real workload with ActivityTimeline for Jira

Knowing what someone has learned only solves half the problem. The other half is knowing how much real work they can actually take on right now, and that’s a question learning tools alone can’t answer.

This is where ActivityTimeline for Jira comes in. It’s a resource and capacity-planning app built directly on top of your existing Jira projects, giving everyone, including new hires, a personal timeline showing what’s assigned to them, along with a workload indicator that reflects how loaded they are relative to their real capacity.

A few features make it particularly useful for managing new team members:

See real workload distribution. The workload indicator, color-coded from light green to red, is calculated from both Jira estimates and custom events such as bookings or training blocks. For a new hire, this means a manager can see at a glance whether an “easy onboarding ticket” is actually filling their whole week or leaving them mostly idle, rather than finding out during a retro two sprints later.

Control allocation for new hires. Rather than assigning tasks the same way you would for a tenured engineer, ActivityTimeline lets you set individual involvement (capacity) per person, for example, configuring a new hire at 4–5 hours/day of plannable work for their first two weeks. Booking events lets you reserve time for shadowing, pairing, or training sessions without needing a Jira ticket for each one, so that time shows up on the timeline and counts against capacity instead of disappearing into an invisible gap.

Avoid overloading during ramp-up. Because the workload indicator accounts for vacations, partial days, and custom involvement schedules, it’s much harder to accidentally schedule a new hire for more than they can handle. If a manager tries to stack tickets onto someone whose involvement is intentionally set to a lower level, the indicator visibly tips into yellow or red before the team finds out the hard way.

The result is planning grounded in actual capacity rather than assumptions. A manager isn’t asking “do I think this person is ready”; they’re looking at a timeline that already reflects training time, partial involvement, and current workload, and making a scheduling decision from there.

Bringing both systems together

Handing someone their first real piece of work comes down to two questions: has the relevant part of their learning path actually been completed, and does the timeline show they have the capacity for it right now? Smart Courses answers the first. ActivityTimeline answers the second. Put together, a manager isn’t guessing anymore; they’re looking at evidence of both readiness and availability before making the call.

Customer Success Manager onboarding

The same model works just as well outside engineering teams. Imagine a company hiring five new Customer Success Managers ahead of a major product launch.

Each new hire is enrolled in a Smart Courses LMS Learning Path that covers product knowledge, support workflows, communication guidelines, and internal tools, with quizzes to verify their understanding before they start working directly with customers. Managers track progress through the insights dashboard, just as an engineering manager would.

At the same time, ActivityTimeline helps team leads reserve time for product shadowing, customer call observations, and coaching sessions by reducing each new hire’s available capacity during their first weeks. As training milestones are completed, managers gradually increase their workload so new Customer Success Managers gain confidence without becoming overwhelmed.

Whether you’re onboarding developers or customer-facing teams, combining structured learning with capacity planning creates a repeatable onboarding process that scales as your organization grows.

Try Smart Courses for Confluence free for 30 days.

Try ActivityTimeline for Jira free for 30 days.

Why do native Confluence tables fail as status tracking tools?

Some teams use Page Properties Reports to create portfolio views. Others rely on large native Confluence tables. Both approaches can work, but as the number of projects grows, filtering, sorting, updating, and maintaining multiple stakeholder views becomes increasingly difficult.
On Confluence Cloud specifically, the Page Properties Report exists in a stripped-down form called the Content Properties Report. Macro nesting isn’t supported, which breaks the more advanced configurations that work on the Data Center. Cloud teams are largely left with a plain native table, and the limitations compound fast.
There’s no way to filter by team or RAG status in view mode, no sorting by deadline or priority, and no grouping by phase. The table shows everything to everyone, which, for a portfolio of 15 or more projects, usually means it shows too much to be useful.

All your projects, one table

Smart Tables for Confluence (Table Filter & Charts) approaches the problem differently. Instead of spreading project information across multiple pages and reports, it keeps everything in a single structured table and adds the interactivity needed to manage it effectively.
One row per project, all data in one place, different stakeholders interact with that same data in different ways without creating additional pages, exports, or versions.

Some of these capabilities are available in other Confluence content formats: inline editing in Live Docs and filtering in Databases.

RAG status that you can actually act on

RAG stands for Red, Amber, Green, a simple health indicator that tells stakeholders at a glance whether a project is on track, at risk, or off track and in need of immediate attention. It’s the first thing anyone looks for in a portfolio review, and the first thing that becomes meaningless when a Confluence native table goes stale.
From there, the whole table responds.
Filter to show only Red and Amber projects before a steering committee meeting and sort by RAG status to surface risk at the top.
Group by status to get an instant count of how many projects are on track versus struggling.
The RAG column stops being a label someone remembered to update and becomes a filter you can query.

Grouping and sorting your portfolio view

As portfolios grow, flat lists become difficult to interpret. Grouping reorganizes the same table instantly by owner to understand workload distribution, by phase to see where projects are concentrated, or by priority to surface what needs immediate attention.
The data stays unchanged; only the view does.
Before a portfolio review, sorting delivers the same speed: by deadline to bring upcoming work to the top, by RAG status to lead with risk, or by last updated date to catch stale projects before they become reporting issues.

Inline editing directly on the page

The biggest reason Confluence tables become outdated is friction. If updating a project requires opening the editor, locating the correct row, making the change, and saving the page, the update gets delayed. And delayed updates compound until the table is no longer trusted.
With Smart Tables, updates happen directly in view mode. A project manager changes the status during a standup. A delivery lead updates a phase during progress review. Small updates take seconds, so they actually happen, and the Confluence table stays current.
Jira remains the right home for tracking work items and operational reporting, but project context, stakeholder updates, and strategic notes live in Confluence, and Smart Tables for Confluence (Table Filter & Charts) make that page interactive enough to serve as the portfolio view too, no switching tools required.

Visualize portfolio health

Smart Tables can also generate charts directly inside Confluence from the same project table, no export, no separate reporting tool needed.
A program manager can visualize projects by phase to see where the portfolio is concentrated.

A department head can view workload distribution across teams; an executive can pull up a RAG status breakdown of how many projects are Green, Amber, or Red as a chart alongside the table, ready for a board update. The chart updates automatically as the underlying data changes, so it always reflects the portfolio’s current state.

It stays connected to the rest of the page

A program manager opens the Confluence table before a portfolio review and sorts by RAG status. Every Red project appears first. An engineering lead filters to their team and groups by phase within seconds; they can see what’s in delivery and what’s still in planning. An executive opens the same page and sorts by priority to focus on the highest-impact initiatives.

Smart Tables also work naturally alongside the rest of a project page: Jira issue embeds, smart links, user mentions, decisions, and other Confluence content, the table remains connected to the broader project context rather than becoming a separate reporting destination.

The best project status table is not the one with the most metrics; it’s the one people actually keep up to date. When filtering, sorting, grouping, and editing are frictionless, the Confluence table stops being documentation and starts becoming an operational tool teams trust.

Building a project status table in Confluence that actually stays up to date is not a process problem. It’s a tooling problem, and one structured, filterable, inline-editable table is usually all it takes to solve it.

Workday manages employee records, approvals, and HR workflows. OnRamp orchestrates onboarding processes across teams and systems. Jira keeps onboarding tasks organized and moving. Together, they replace spreadsheets, scattered Slack messages, and forgotten follow-ups with a structured process.

But there is a problem many teams eventually run into.

A new hire can complete every onboarding task, receive every account, attend every scheduled meeting, and still not actually be ready to do the job.
That is because onboarding logistics and onboarding learning are two completely different things. You can process an employee without properly preparing them.

Where operational onboarding ends

Most modern organizations already rely on a stack of tools to manage onboarding at scale.
Workday handles employee records, approvals, and HR workflows.
OnRamp coordinates onboarding journeys across teams and systems.
Jira tracks tasks, tickets, and operational execution.
Together, they remove the chaos of manual onboarding, replacing spreadsheets, Slack threads, and ad-hoc coordination with structured, automated workflows.

But even when all of this works perfectly, a gap still remains.
A new hire can complete every onboarding task, receive every account, attend every scheduled meeting, and still not actually be ready to do the job.
That is because operational onboarding and learning onboarding solve two fundamentally different problems.

Operational Onboarding vs Learning Onboarding

Operational Onboarding:

These systems measure whether onboarding tasks happened.
A completed Jira ticket confirms that access was granted.
A completed HR workflow confirms that approvals were processed.
But neither confirms whether the employee is actually ready to perform their role effectively.

Operational onboarding is about execution:

• Accounts created
• Access granted
• Equipment delivered
• Workflows completed

It ensures the employee can enter the system.
But it does not ensure they can perform inside it.
Learning onboarding fills the gap left by operational systems.
Most organizations already have onboarding knowledge documented inside Confluence. The problem is structure.
New hires are often handed dozens of pages without knowing:

• Where to begin
• What matters most
• How information connects

So instead of learning a role, they end up having to navigate documentation.

Operational onboarding creates access.
Learning onboarding creates understanding.
Operational onboarding answers: “Are they set up?”
Learning onboarding answers: “Are they ready?”

Smart Courses for Confluence: turning documentation into learning

Smart Courses for Confluence transforms Confluence from a documentation platform into a structured learning environment built around the knowledge your team already maintains there, not a separate LMS you have to migrate content into.

That distinction matters.

In most organizations, onboarding knowledge evolves constantly alongside the business. Smart Courses keeps the learning experience connected to the same Confluence environment employees will use long after onboarding ends.

Instead of navigating isolated wiki pages on their own, new hires progress through a well-organized catalog with course cards and structured learning paths with clear progression and measurable outcomes.

Assign courses: New hires are automatically enrolled based on their group, so learning starts on day one without anyone needing to set it up manually. Once they join the group, they will receive a notification to take the course.

Exams and quizzes: comprehension gets verified at each stage, which matters most for compliance, security, and product knowledge, where misunderstanding has real consequences

Certifications: employees earn a record of what they have completed, and managers can see who is genuinely ready, not just who has finished the tasks

Learning paths: onboarding is organized into a guided progression so new hires move through knowledge in the right order, from foundational concepts to role-specific expertise, instead of navigating pages on their own

Skills and prerequisites: courses can require specific knowledge or completed modules before unlocking the next stage, ensuring no one skips steps they are not ready for.

How Workday, OnRamp, Jira, and Smart Courses work together

These tools complement each other so effectively because each solves a different onboarding problem.

Workday manages the employee record and HR workflows

OnRamp orchestrates onboarding journeys and cross-team coordination

Jira manages operational execution and task tracking

Smart Courses manages the learning layer that transforms documentation into structured onboarding and measurable capability development

A new employee can be created in Workday, automatically enrolled in onboarding workflows through OnRamp, assigned operational tasks in Jira, and guided through structured learning paths in Confluence via Smart Courses.

Operational onboarding and learning onboarding become connected rather than isolated from each other.

The Use Case: Onboarding a senior backend engineer

Move the engineer from “signed contract” to “shipping their first line of code” in 10 days, while ensuring they understand security protocols and system architecture along the way.

Phase 0: Workday the HR trigger

Everything starts in Workday.

Once HR marks the candidate as “Hired,” the employee record is created and synchronized across systems. Role, department, and onboarding metadata are now available to the rest of the stack.

This is what officially triggers the onboarding process.

Phase 1: OnRamp the orchestration layer

From that moment, OnRamp takes over coordination.

It connects HR, IT, and engineering teams into a single onboarding flow:

IT is notified to prepare provisioning
HR receives compliance tasks
Managers get onboarding checklists
The new hire receives timelines and communication
Jira onboarding projects are automatically prepared

At this point, onboarding is no longer manual it is orchestrated across systems.

Phase 2: Jira, the operational execution layer

Next comes execution.
A Jira onboarding project is automatically created and populated with tasks across teams.
IT provisions a MacBook Pro, GitHub access, and AWS permissions.
Managers are reminded to schedule onboarding sessions and introductions.
Security teams handle access reviews and compliance approvals.
Everything that needs to be physically and operationally set up is now tracked and completed.
But even when everything is marked as done, a gap remains.
Jira confirms the engineer is equipped not that they are ready.
They may have the laptop, the access, and the tickets completed… but still not understand deployment safety standards or backend architecture principles.

Phase 3: Smart Courses for Confluence, the learning layer

This is where onboarding shifts from execution to understanding.
Instead of navigating a long list of Confluence pages, the engineer enters a structured learning path built directly from the company’s existing documentation.
They are guided step by step through the knowledge they actually need to perform the role.
At the end of the “Security Standards” module, they complete a short quiz to validate understanding.

Once completed, Smart Courses generates a certification:

“Learning Path Complete: Security Certified.”

In Confluence, training materials often end up scattered across pages, inconsistently formatted, and difficult to navigate. As content grows, users lose visibility, and administrators lose control over structure and consistency.

Smart Courses for Confluence solves this by turning Confluence into a structured training system where teams can build a fully customized learning catalog, define clear Learning Paths, and control how content is discovered, filtered, and consumed.

Building a structured training system

The main shift Smart Courses introduces is moving from unstructured documentation to a designed learning environment.

Instead of isolated pages, training content is organized into structured learning elements, including courses, exams, Learning Paths, and a centralized catalog. This allows organizations to design training intentionally, ensuring consistency across teams while maintaining flexibility to accommodate different learning needs.

As a result, training becomes easier to manage, easier to scale, and significantly easier for users to follow, since content is no longer fragmented but part of a clear learning journey.

Building a customized training catalog

One of the most important aspects of delivering a strong training experience is customization.

Smart Courses allows teams to customize its catalog views based on their specific needs. The catalog can be adapted to reflect internal structures, training priorities, and audience segmentation.

This flexibility is essential when thinking about how to build a learning system in Confluence that scales across teams and departments.

Filters

Discoverability is where most training systems fail and where Smart Courses delivers the most impact.

The catalog includes a powerful filtering system that allows learners to find content quickly based on:

• Type (courses, exams, Learning Paths)
• Category
• Difficulty
• Language
• Status (assigned, ongoing, done, and favorites)

These filters transform the catalog into a dynamic discovery tool. Instead of searching manually, learners can navigate training logically and efficiently.

This directly addresses the core issue: making training content not just available, but easy to find.

Beyond structure: customizing the training experience

Customization in Smart Courses for Confluence goes beyond organizing content; it defines how training is experienced.

Teams can brand the catalog with logos and titles, and add announcement messages (info, note, or warning) to guide users directly within the interface. This transforms the catalog from a simple page into a dedicated training environment.

Administrators can also control how content is prioritized by setting default sorting and featuring up to 20 courses, ensuring the most important training is immediately visible.

On the visual side, course cards can be customized to show or hide specific information, while layout settings such as thumbnail size and scaling keep the catalog clean and consistent.

At the same time, categories and difficulty levels bring structure to the experience. Categories can be created without limitation, allowing teams to organize content by topic, department, or training objective. Difficulty levels, defined up to ten levels, introduce a clear sense of progression by indicating course complexity.

Together, these capabilities turn the catalog into a structured, branded, and fully controlled training experience, not just a list of content.

Improving discovery, structure, and learning experience with ecosystem tools

Beyond Smart Courses itself, the training experience becomes more powerful when supported by complementary tools that enhance the Confluence environment.

Rovo AI by Atlassian improves content discovery by helping users surface relevant training materials and documentation through intelligent search and contextual recommendations across Confluence and connected apps. Instead of relying solely on manual navigation, users can ask natural queries and quickly find useful knowledge across their organization.

Refined sites by Refined transforms Confluence into a fully branded training portal by improving navigation, layout, and overall user experience. This creates an environment that feels like a purpose-built training platform rather than a traditional documentation space, which increases engagement and usability.

On the content-structure side, scroll content manager by K15t helps teams manage training documentation in a scalable, consistent way. It ensures that content remains properly structured, version-controlled, and easy to maintain as training programs evolve.

To reinforce consistency, Synced Blocks Macro for Confluence allows teams to reuse content across multiple training pages while keeping it synchronized.

For presentation and usability, Aura Content Formatting  Aura Apps (Seibert – appanvil) improves the visual structure of training content by introducing layout components that enhance readability and reduce cognitive load, making learning materials easier to consume.

Finally, Composition Tabs by Appfire for Confluence helps organize complex content into structured sections using tabs, allowing learners to navigate information more easily without being overwhelmed.

Together, these tools enhance the broader Confluence environment in which Smart Courses operates, improving discovery, structure, consistency, and usability around the training experience.

Most teams start using Confluence tables with high hopes. They create pages to track KPIs, monitor performance, and share updates across teams. At first, it works.

But over time, things break down.

Data gets outdated, pages get duplicated, and metrics such as KPI lose consistency. Eventually, teams move their tracking back to spreadsheets.

This isn’t a team problem. It’s a tooling gap.

And it becomes especially visible as organizations try to scale Confluence KPI tracking and project management in Confluence.

The problem with native Confluence Tables

For some teams, a typical KPI table in Confluence looks like this: rows for campaigns or initiatives, columns for owners, deadlines, statuses, and metrics. It’s a reasonable starting structure. But the moment the dataset grows, the cracks appear fast.

Native Confluence tables offer limited filtering and grouping capabilities. You can’t easily filter by owner or status, group by team or priority, or dynamically sort large datasets. Updates rely entirely on people remembering to come back and edit the page.

So teams compensate in predictable ways, duplicating pages for different views, exporting to spreadsheets, and maintaining multiple versions of the same dataset just to answer simple questions.

Smart Tables: a structured layer inside Confluence

Smart Tables addresses the root limitation directly. Rather than treating Confluence pages as documents with embedded tables, Smart Tables turns those tables into interactive, structured datasets without requiring teams to leave the workspace.

The shift sounds subtle. Its effects are not.

• Filtering
  Each stakeholder sees only their slice of data, by team, status, quarter, or priority. What makes this powerful is that filters are persistent, reusable views built on top of a consistent schema, so they never break and always reflect live data. One table replaces what used to require multiple duplicated pages, each drifting out of sync.

• Grouping
  As KPI data grows, a long flat list of metrics becomes impossible to scan for different teams, statuses, and priorities all mixed together with no visual hierarchy. Grouping solves this by organizing data into meaningful categories on the fly. Group by team to see how each department is performing at a glance. Group by status to instantly separate what’s on track from what’s at risk. The data doesn’t change just how you navigate it.

• Sorting
  Without sorting, the answers to the most critical questions, which KPIs are underperforming, which campaigns are delivering, and what needs immediate attention, are buried inside the data. Sorting brings them to the surface instantly. Sort by lowest performance to identify risks before they escalate. Sort by highest impact to highlight wins worth sharing. Sort by deadline to stay ahead of what’s coming. Any field, any direction, actionable in seconds.

The foundation of effective Smart Tables tracking is a consistent data structure. Each row represents a single unit of measurement: a campaign, a sprint, or a product initiative. Each column is a defined, standardized field: metric name, owner, team, status, priority, reporting period, performance value.

When every row follows the same schema, the entire table becomes a queryable dataset; that consistency is what transforms a table from a formatted list into a system.

The Atlassian Teamwork Collection: tools becoming a system

With the Atlassian Teamwork Collection, the company is making a deliberate architectural shift: away from individual apps used side by side toward a unified system where planning, documentation, and execution are deeply connected.

This reflects something real about how work actually happens. A decision made in a Confluence page triggers a project tracked in Jira. A sprint outcome updates a KPI that lives in a doc. When tools are isolated, context is lost at every handoff. The Teamwork model is designed to close those gaps.

Even within a better-connected Atlassian ecosystem, Confluence had a specific problem: the moment documentation became operational, tracking deliverables, monitoring KPIs, and managing live project data, its tables became a liability. Static by default, prone to drift, dependent on manual exports. The Teamwork vision needed Confluence to do more.

The bigger shift: from documentation to operations

Together, Smart Tables and the Teamwork Collection represent a broader transformation in how teams manage work.

Reporting consistency, one of the most persistent pain points in project management, gets addressed at the source. KPIs are defined once in a structured format in Confluence. Every stakeholder sees the same data in the same format. Reports are generated from the live source, not assembled from exported fragments.

Just as importantly, this shift doesn’t require teams to change how they work inside Confluence.

Smart Tables works effectively with native Confluence macros and elements, including smart links, attachments, code snippets, decision macros, and user mentions. Tables remain fully integrated with the rest of the page, whether it’s linking to a Jira issue, displaying media, or exporting to PDF.

What this means in practice

A team lead filters the KPI table in Confluence to view only their team’s metrics. A manager groups data by status to spot risks, while an executive sorts by performance to identify priorities before a review. No exports, no duplicate reports, no need to search for the latest version.

This is the experience that Smart Tables enables and that the Atlassian Teamwork Collection is designed to support.

Confluence KPI tracking isn’t about adding more tools or pages. It’s about making existing data structured, consistent, and interactive, with Smart Tables providing the foundation and Atlassian delivering the system that connects it all.