Product updates

You can now share any Swarmia AI chat with people in your organization, so they get the full context, follow-up questions, and the reasoning behind your conclusions.

The new initiative forecast runs a Monte Carlo simulation on your team’s recent activity to estimate the most likely completion date and the remaining FTE for any in-progress issue or initiative.

Flow efficiency is now available as an aggregate in issue metrics and explore. You can roll it up to compare how your teams perform across epics, stories, or tasks — and see how they measure against Swarmia’s industry benchmarks.

Engineering effort has a price tag, and now you can see it in Swarmia — in real currency, so you can talk about investment in terms the rest of the business understands.

Earlier this year, we introduced AI categorization for issues, followed by AI matching of pull requests to issues. Now, AI categorization also handles pull requests that aren’t linked to any issue.

Our new email digest brings a snapshot of your engineering organization to your inbox once a month, so you can see where things stand in seconds and dive into Swarmia when something catches your eye.

You can now create computed columns in the explore view — dividing one column by another, combining metrics, or building on top of previously computed columns to get the exact metrics you need.

Building and customizing reports in the explore view just got a lot more intuitive. We redesigned the filtering experience and added chart visualizations, so you can spend less time wrestling with your data and more time taking action based on it.

Key metrics lets you select the indicators that matter most to your organization and pin them to the Swarmia front page. Every time someone logs in, they see the same shared view of your company’s engineering performance.

The new scope filter for investment balance breakdowns allows you to zoom in on a specific team, focus on a single issue type, or see how a particular slice of work breaks down across categories.

Swarmia now automatically identifies which pull requests have been reviewed by AI agents and flags those reviews separately. This gives you the visibility you need to drive adoption, evaluate agents against each other, and understand how they’re affecting your team’s flow.

Merged PRs per FTE is a new metric in code metrics that normalizes your team’s merged pull request count by engineering capacity. This makes it easier to compare throughput across teams of different sizes and track whether process changes are driving real improvements.

The focus summary in Swarmia helps you understand where your teams are spending their time. Now, you can drill down even further to see how that work actually unfolded across commits, pull requests, and comments with the activity timeline.

Setting up your team structure in Swarmia just got easier. You can now import and update teams and membership in bulk using a CSV file, no GitHub teams or API setup required.

You can now filter pull requests by their target branch (the branch they’re merged into) anywhere in Swarmia. We’ve also renamed the existing branch filter to source branch to make the distinction clearer.

With Swarmia’s new MCP server, you can query your Swarmia data directly from MCP-compatible AI assistants like Claude, Cursor, and other tools you already use.

Swarmia has always linked pull requests to issues automatically when developers include the issue key in their PR. Now, we’re adding AI-powered matching to catch the ones that would’ve previously slipped through the cracks.

Swarmia AI allows you to ask questions about your data in plain language and get answers that combine insights from across the product. The responses can include summaries, tables, and charts.

The new explore view lets you build, customize, and save reports that show the exact data you need, whether it’s a combination of several metrics, a simplified version of a report, or a drill-down into a specific problem area.

Swarmia now supports GitLab as a code hosting platform. This opens up Swarmia to engineering organizations that use GitLab, whether it’s your only code hosting platform or you’re using it together with GitHub.

We’re introducing a new details tab in the issue view, with a cycle time breakdown that shows exactly how long an issue spent in each stage of development.

The work tab in investment balance now uses the same listing as focus summary — making it easier to explore your biggest investments at any level of the organization.

We’ve revamped the GitHub Copilot activity view to give you more granular and accurate data on how your organization is using AI.

We’ve made several improvements to the issue and initiative timeline to help you visualize the work that actually matters to you.

We’re extending our Claude Code support. The new integration uses Claude Code’s OpenTelemetry monitoring and makes Swarmia compatible with every way you can run Claude Code: Claude Console, Team or Enterprise plan, as well as cloud providers.

You can now import time-off data through our API, giving you another way to maintain precise effort calculations for investment balance insights and software capitalization.

You can now toggle automatic categorization for uncategorized work in your investment balance breakdowns. Instead of manually creating rules for every edge case, Swarmia analyzes each issue’s description, linked issues, and other metadata to find the most suitable category.

You can now see exactly which parts of your codebase are changing and when. The new codebase view aggregates all file changes from pull requests into a tree structure, making it easy to spot patterns and explore your code activity.

You can now compare your engineering metrics against Swarmia benchmarks and your team against the organization average. This makes it easier to spot improvement areas and identify which teams are doing well.

We’re launching beta support for connecting both Linear and Jira to Swarmia at the same time. Now you can get comparable metrics and insights across both tools, helping you bridge the gap when teams are using different systems.

AI coding agents create pull requests end-to-end, not just suggest code in your editor — they plan work, write code, run tests, and respond to reviews. Swarmia’s new AI agents view helps you see how these agents are contributing across your organization.

You can now view metrics using percentiles instead of just averages. In the code metrics view, you’ll find a new dropdown that lets you switch between different aggregation methods, including median (p50), p75, p90, p95, and p99.

You can now see how survey scores have changed across multiple surveys with the new trend charts. Instead of comparing just two surveys at a time, you can now track progress over many surveys to understand whether things are moving in the right direction.

We’ve reorganized Swarmia’s navigation to make features easier to discover. Related metrics and views are now grouped together, so you can find what you’re looking for without hunting through menus.

The new initiatives breakdown gives you an idea of which teams are actively contributing, how much effort each has invested, and how their work is progressing.

You can now see how pull requests assisted by different AI coding tools — or no AI tools — perform across metrics like throughput, cycle time, batch size, and review time. You’ll find this and all the AI adoption, activity, and impact views under the new AI impact section in the main navigation.

Swarmia now automatically detects pull requests assisted by GitHub Copilot, Cursor, or Claude Code. This helps you understand how AI use affects developer productivity metrics, such as pull request cycle time, throughput, and batch size.

You can now use Swarmia notifications in Microsoft Teams to boost your team’s work and improve collaboration without switching between tools.

You can now save a set of filters as a shared view in the initiatives overview. This makes it easy to keep an eye on the initiatives that matter most to you and share curated views with your teammates.

You can now see time off directly in the work log. When you group by author, yellow annotations show when team members are away. This helps you understand activity patterns without pinging colleagues while they’re out.

We’re introducing a new event type called issue progress days to our effort model, making it possible to assign effort to work that isn’t associated with Git activity.

You can now track Claude Code adoption and activity patterns directly in Swarmia, along with your GitHub Copilot and Cursor data.

You can now define how linked work items should be included in your Swarmia initiatives. This makes it easier to track cross-team work, especially if you’re using Jira Plans (previously Advanced Roadmaps) or Jira Product Discovery.

We’ve added two new roles to Swarmia: the viewer role is perfect for team members who need visibility into engineering work but shouldn’t make configuration changes, while the team admin role is intended for managers who need to configure team-level settings but don’t need full admin access.

You can now reorder your investment balance breakdowns and change which one is primary. Simply drag and drop the breakdowns in settings → investment categories to reorder them. The first breakdown in the list becomes your primary breakdown.

You can now use Microsoft Entra ID authentication to manage your organization’s access to Swarmia. This is especially useful if you’d like to invite non-engineers, like the leadership team, product managers, designers, or finance team members.

We now support automatically syncing initiatives from Jira. If your organization tracks high-level projects in Jira, you can set up Swarmia to automatically display them in the initiatives view.

The newly updated initiatives overview gives you instant visibility into project progress and team focus.

Now you can see detailed activity patterns for GitHub Copilot and Cursor across your organization. Track engagement levels, understand where AI suggestions are gaining traction, and identify teams that might need extra support.

Now you can import time off data directly from a CSV file, making it easy to maintain accurate effort calculations regardless of your HR setup.

Onboard your team members to Swarmia faster with native Slack invites that automatically enable GitHub-Slack notifications — the main way individual engineers interact with Swarmia.

Keep pull requests small with batch size working agreements. Plus, organize survey questions with custom topics, control Jira project access, and see total team effort in focus summaries.

Swarmia users can now see their investment balance breakdown in the sprint view. Also, Swarmia now supports Linear Project labels, bringing consistent labeling across issues and projects.

We now support Cursor in Swarmia’s AI assistants view. If you’re using Cursor and GitHub Copilot, you can now see both tools side-by-side and track adoption patterns across your engineering teams.

You can now use pull request and issue filters to define what counts as a hotfix in Swarmia. This gives you more control over change failure rate calculations and helps ensure the metric reflects your team’s actual fix patterns.

Now you can add manual notes to pull requests and issues to capture any missing context. These notes help your team understand what really happened behind the metrics.

Software capitalization helps you automatically categorize engineering efforts as either capital expenses (CapEx) or operating expenses (OpEx) and generate reports for your finance team.

AI coding tools like GitHub Copilot can significantly boost developer productivity, but how do you know if your investment is paying off? Now you can track GitHub Copilot adoption and usage across all your teams over time.

When you merge a pull request that isn’t linked to an issue, the Swarmia Slack bot will now suggest relevant issues based on your pull request details. The suggestions are powered by AI that analyzes your PR and issue metadata to find the most likely matches.

Swarmia now supports automatically grouping similar issues together so you can identify common themes without the manual work.

The sprints view in Swarmia is now faster and offers even more insights. With the latest updates, you can quickly jump from analyzing long-term trends to drilling into what’s happening during each sprint.

Our new issue metrics view gives engineering leaders a comprehensive overview of how work flows across the entire organization.

We’ve refined our developer effort model based on your feedback and extensive testing. In this changelog update, we share what has changed.

Signals proactively surface insights about your team’s work. Instead of you hunting for patterns, signals bring them directly to you, along with recommendations for what to do next.

You can now connect Swarmia with your on-premise GitHub Enterprise and Jira instances even when they’re not publicly accessible.

Your existing Linear initiatives are now automatically imported to Swarmia’s initiatives view, making sure you always have real-time visibility into cross-team engineering work.

Create initiatives faster with the new issue filters that allow you to quickly gather all related tasks into an initiative.

You can find the new search from the navigation bar or hit ⌘K (or Ctrl+K on Windows) to start searching from anywhere in the app.

You can now use Google authentication to manage your organization’s access to Swarmia. This is especially useful if you’d like to invite non-engineers to the app.

The survey results heatmap now supports comparisons to the survey average, industry benchmarks, and your other surveys.

Swarmia now automatically sends Slack reminders to people who haven’t responded 7, 3, and 1 day(s) before each survey closes.

The new focus summary shows how much of a team’s effort goes to the top prioritized initiatives, projects, epics, and stories over the selected time period.

Now you can add your own questions to adapt the surveys to a wider range of situations and ask about things specific to your organization.

The FTE-based effort model is now also available in the investment balance. To get started, simply navigate to balance in the menu and toggle to effort above the investment balance chart.

Introducing a new sprint view to help Scrum teams plan and analyze their sprint activity more effectively

Now, you can see relevant survey questions right next to your pull request data, issue insights, and DORA metrics in Swarmia. Along with them, we show the latest survey results for the selected team to help you analyze everything in one place.

The new model measures effort in full-time equivalent (FTE) months. The advantage of this approach is that it considers hundreds of data points for each developer and accounts for different coding styles.

Questions & comments tab in surveys lets you analyze survey feedback in one place. View survey results in more detail, filter, sort, and take informed actions based on your findings.

The new navigation makes it easier to access team and organization-level features so you can quickly access the tools and insights you need

The new team management API helps you automate managing your organization’s team structure and improve data quality by keeping your team structure up to date.

Identify areas that need attention and take action by sharing survey results with your teams

You can now use the initiative forecast feature to estimate the end date of an initiative based on three inputs: total number of epics, average epic cycle time, and average number of epics in progress.

You can now look at DORA metrics for all teams with Swarmia's organization insights view.

We've made it easier to define production environments in Swarmia, enabling more accurate DORA metrics. You can set global rules or define production environments per deployment app.

We’re introducing additional breakdowns to the investment balance view to make it easier to answer questions like: how do we reduce reactive work?, how much are we able to focus on our key initiatives?, and how much are we investing in a specific product area?

We’re excited to announce the public beta of developer experience surveys: a better way for you to collect high-quality developer feedback and combine it with the system metrics and visualizations you already have in Swarmia.

Swarmia allows you to reliably measure, visualize, and export software development data.

View pull requests linked to an issue and all of its subtasks

Run a surveys based based on Swarmia’s survey framework, with questions ranging from team focus to managing technical debt

If your organization is using Okta Single Sign-On, you can now use it to manage user access to Swarmia.

Our latest update makes uncategorized work more visible in the investment balance view and brings you AI-powered suggestions for categorizing work.

Understand the cycle time of long-running pull requests with the new real-time pull request activity timeline in Swarmia.

Drive strategic projects with confidence using Swarmia

Unreliable CI/CD setups can result in hours of waiting time per developer per week, and it only gets worse as the organization scales, translating into six-figure losses and weeks of idle time in larger organizations.

Strategic projects can be particularly challenging since they often span months and involve multiple engineering teams.

Unreliable CI/CD setups can result in hours of waiting time per developer per week, and it only gets worse as the organization scales, translating into six-figure losses and weeks of idle time in larger organizations.

We continue to enhance organizational insights. This time, we’ve included comparisons with the previous time period for all organizational metrics in Swarmia.

Our new major update delves even deeper into helping engineering leaders understand investment patterns in engineering teams and the entire organization.

Crete and manage hierarchical team structures in Swarmia

Create and manage hierarchical team structures in Swarmia

Developer Overview makes the work of individual developers visible without surfacing any data that could be misused. It allows devs and their managers to have better conversations and maximize learning and impact.

We’ve been working on one final piece of the deployment insights puzzle: supporting GitHub Deployments as a data source.

Deployment insights summary: Single view with all four DORA metrics, simpler configuration, and automatic change failure detection.

Shipped in January: new working agreement feedback loops and updates to how we help you measure DORA Change Failure Rate

This December has been all about bringing DORA metrics to the next level, ensuring teams can get an accurate view of their deployment process, and follow change failures and time to recovery no matter how they deploy.

You may want to adjust team ownership when a team member works across multiple teams, or some PRs include exploration work that you don't like to be considered in PR-related metrics and alerts.

You can now choose to base team membership on GitHub teams, add team members one by one, or do a combination of both

In the new organization-level code insights, you can see key metrics across multiple teams, including cycle time, review rate, review time, throughput — and more.

With our latest update, in addition to importing teams from GitHub, you can also create and manage teams in Swarmia. Now you have more flexibility in managing team data without making changes to your GitHub organization.

You can now use flexible filters in issue insights to filter data by label, status, issue key, and issue type.

Now the timeframe you select in Swarmia is preserved across all insights views as you navigate the app, and timeframe presets are more readily available.

Investigating cycle time issues just got easier with the new cycle time breakdown for individual pull requests.

Today, our Linear integration is officially out of beta, immediately available to connect in the Swarmia app.

With our latest update, you can respond to GitHub comments without leaving Slack. The bot's rich line-by-line comment previews make sure you have sufficient context to respond.

With the latest update, we introduce more ways to auto-categorize pull requests, adding filters by label, repository, branch name, title, and status to investment category configuration, increasing the accuracy of investment insights.

We've improved our deployments insights, adding MTTR (mean time to recovery) and change failure rate for complete coverage of DORA metrics.

We improved how Jira issues are mapped into issue types in Swarmia and how issues are assigned to teams.

We improved the logic behind investment categories to help teams make better investment decisions with Swarmia.

With our new batch size insights, you can see how pull requests are distributed by size and spot patterns in the review process and pull request flow.

Some work can be automatically categorized with our investment categories and pull request filters. Alternatively, you can manually link contributions, giving you flexibility and control over your data in Swarmia.

We’ve made it easier to dig deeper into individual pull requests anywhere in Swarmia. Now you can select any PR in Insights, and work log to get more context.

You can now filter work log by investment category — up to individual commits — in a calendar view. Use it to get insight into how daily decisions affect the investment distribution.

Our latest update brings working agreement insights to more places in the app, and improves our Slack digest to make it easier to focus on that one pressing issue the team agreed to improve on.

With the new investment insights, you can track any custom categories in Swarmia, and get an accurate, highly customizable view into how teams spend time.

You can now see issue completions as dots in the work log. This allows you to see work without code commits and gives you a better sense of how projects are moving forward.

Celebrate when you get a larger project completed with a new team notification. Get a summary of the key metrics like scope creep, active days, longest-running tasks, and more — right in Slack.

Swarmia’s new investment distribution view gives transparency to the different areas of work teams focus on to help you achieve a balance in how the time is spent.

Swarmia’s holistic approach has gotten even more complete with the addition of deployment insights. Now you can see deployment frequency, average deploy time, and deploy success rate in Swarmia.

With the latest update, it's possible to select multiple teams in pull request insights to see how individual teams' WIP and cycle time trends compare to the rest of the organization.

Use the new issue insights to get an overview of cycle times, scope size, and scope creep for all ongoing and completed issues.

Today we're excited to introduce new tools to help you diagnose flow issues, recognize scope creep signals early on, and improve planning accuracy.

With our latest update, you can choose what comments and PR-related updates you want to be notified about.

Our new pull request insights help you better understand the process changes that improve velocity and quality.

Our new pull request archive gives you the option to hide old and stale pull requests in Swarmia. This is especially useful for you to start focusing on improving ways of working when adopting Swarmia without letting the burden of the past get in your way.

Our new working agreement helps track all commits merged to your main branch without review, and start a conversation within the team if it becomes an issue.

Now you can link pull requests to investment categories automatically by adding a rule to auto-assign work to categories based on PR titles.

With the new cycle time breakdown in Swarmia, it's easy to see whether review, merge, or WIP time takes longer than expected.

With the new high-level work log, you can easily zoom out and see everything you worked on over the past year. Use it to diagnose flow interruptions, spot never-ending projects, and prepare for team retrospectives.

With our latest improvements, you can immediately tell from the Slack notification if your PR is good to go or has anything left to improve.

We’ve added new essential filters providing an at-a-glance overview of all pull requests in both personal and team context.

Now it’s even easier to prevent future exceptions to your working agreements as you can keep track of all that escapes your agreements. Aim for inbox zero, and review your agreements with the team frequently to make sure the new habits stick.

We made the Daily Digests on your team's Slack channel even more actionable and concise than before.

See all completed, in progress, and to-do subtasks in a progress bar below each issue in work log. Now it easier to stay up to date with the issue scope, and status of subtasks in your projects.

This week, we’re releasing new features that help you drill down to the pull request review time, and to set targets for issue cycle times.

We've made multiple updates to managing and adopting new Working Agreements.

This week we’re introducing a powerful new feature to categorize pull requests without linking them to issues.

The all-new Issue Insights feature lets you drill down deeper on an individual Epic, Story, Task or Bug to find out how your team organizes around issues, and what you could do to increase focus and accelerate delivery.

Our first iteration of Working Agreements includes features to manage the amount of work in progress and the cycle time of Pull Requests.

The new cycle time insights plots completed issues on a timeline and shows how long they were open. The scatter plot makes it easy to identify outliers and trends, and drill down on individual issues.

This week we are adding Quality Insights to help teams stay on top of their Continuous Integration pipelines, and working on all new Insights about flow.

Flow Insights plots the number of open Pull Requests, Epics, Stories and Tasks on a timeline, helping teams understand how much work they have on their plate at a given time.

We're starting to develop a new product area called insights to help teams form a holistic view of their ways of working. The first insights are about quality: bugs and continuous integration.