What is Swarmia?

Both. Swarmia is an engineering intelligence platform, which Gartner calls a developer productivity insight platform. Gartner previously called the category software engineering intelligence, and buyers use the names interchangeably. Other category names we commonly hear are engineering management, developer experience, engineering effectiveness, engineering metrics, and software development analytics. Whatever the label, the job is the same: connect data from the tools engineers already use, so leaders can see how work flows, where time and money go, and what to improve.

Swarmia is built for engineering leaders: VPs and Heads of Engineering, Directors, and CTOs who need answers about their organization without stitching them together from fifteen different tools. Engineering managers use it for local improvements and one-on-ones, and finance teams use it for audit-ready capitalization reports. Because most data is visible to everyone, engineers use it to improve their own work, not to be watched.

Yes. Swarmia is modular, so you can start with one use case and add more over time. The four modules are AI adoption and cost, developer experience surveys, productivity and AI, and software capitalization. The Standard plan includes all four, plus cross-domain insights such as connecting survey responses with system metrics. Read more about plans and pricing.

Swarmia believes engineering can produce better business outcomes (think revenue) when you fix the system people work in, not when you measure individuals harder. An engineer fixing a bug three times faster doesn’t matter much if that bug still waits ten hours on coordination, triage, and Slack threads before anyone touches the code. Swarmia’s framework splits engineering effectiveness into three areas: business outcomes, developer productivity, and developer experience. We’ve written a book called Build, which covers it in full.

Yes. Gartner named Swarmia as a Leader in its first Magic Quadrant for Developer Productivity Insight Platforms in May 2026.

Engineering organizations from fast-growing scaleups to large enterprises use Swarmia. Our reference customers include Supabase, Miro, and Bolt.

Yes. Swarmia runs on one org structure and one data model across every team, so a team lead and the CTO look at the same numbers. We have a growing number of customers with 1,000+ software engineers, and can provide introductions to their engineering leaders upon request. Security and access questions, including SSO, role-based access, and data residency, are covered in the security section below.

Swarmia measures AI impact by comparing AI-assisted work with everything else on the same delivery metrics: cycle time, throughput, and delivery speed. You can filter any engineering metric by AI usage, so the question moves from “are people using AI” to “is AI helping us ship faster and better software.” Usage data comes from the AI tools, and delivery data comes from your code hosting platform and issue tracker.

Swarmia tracks adoption and usage for GitHub Copilot, Cursor, Claude Code, Codex, and Devin, plus AI review tools such as CodeRabbit and Greptile. See the full list of integrations. Any other AI coding tool, including one you built in-house, can be added as a custom integration, either by linking the Git identity it commits under or by pushing daily usage data through Swarmia’s API.

Yes. Swarmia shows who has access to each AI tool and who’s actually using it, side by side, so you can find and eliminate unused licenses. AI cost is shown per team and per person as the list price of the tokens used, which gives a comparable measure across tools but can differ from your bill on subscription plans or negotiated rates. Seat license costs aren’t included. Read how Swarmia calculates AI cost.

AI coding tools speed up individual engineers, but delivery depends on the whole system around them. If review times double because there’s twice as much code to review, the gain disappears before it reaches customers. Swarmia shows where work waits: in review, in progress, or between teams, so you can see whether AI gains reach delivery or get absorbed along the way.

Yes, at the level of pull requests and files. Swarmia shows which pull requests involved an AI agent and which parts of the codebase each tool changed, without reading source code. You can browse those changes by tool and export the data for your own hotspot analysis. Swarmia doesn’t estimate the exact share of AI-written lines, because that’s hard to measure with high certainty.

Yes. Swarmia ties AI cost to the work it produced, such as how many full-time equivalent months and how much AI spend went into a specific epic, project, or story.

Swarmia shows repository-level readiness signals, such as whether repos have agent instruction files and how those files change over time.

Swarmia tracks research-backed engineering metrics, including DORA metrics, cycle time, throughput, review time, work in progress, and much more. Every metric breaks down by team, with historical trends, and you can drill into what’s driving each number.

Swarmia focuses on improving developer productivity at the team and system level: how work flows, where it waits, and how fast feedback loops close. While we’ve intentionally prioritized surfacing system and team level metrics in the UI, Swarmia AI and Swarmia MCP also allow you to pull any data you’re interested in per engineer.

Swarmia shows individual activity, such as pull requests, reviews, and issues, to everyone on the team, including the engineer, but it doesn’t score individual productivity. It doesn’t track keystrokes or screen time either. Metrics and working agreements are built around teams, because that’s where improvement happens. We’re also happy to hide any individual-focused views from the UI upon request.

Swarmia turns metrics into habits with signals, working agreements, and Slack or Microsoft Teams notifications. Teams set their own targets, like reviewing pull requests within 24 hours, and Swarmia notifies the right people when something slips. Signals surface trends, such as review times doubling on one team, before they become problems.

Yes. Swarmia’s investment balance shows how engineering effort splits across categories of work, such as new features, maintenance, and keeping the lights on. Swarmia applies the categorization rules you define first, then uses AI to categorize the remaining issues from their descriptions and linked issues. It uses the same effort model as software capitalization, so nobody has to fill in timesheets.

Yes. Swarmia tracks initiatives, so leaders can see whether big projects are on track early enough to change course. It also shows what teams actually complete, which makes the next plan more realistic.

Yes. Swarmia AI answers questions about your engineering data in natural language, such as “which teams have the most pull requests waiting for review right now.” You can save answers as custom reports, or connect your own AI tools to Swarmia through MCP and the API.

Swarmia’s developer experience survey measures the parts of engineering work only engineers can report on. The framework has 37 research-backed questions developed with psychometrics experts, and you can freely remove any questions or add your own. Setup needs no code hosting connection, just Slack or Microsoft Teams and your team structure.

When a survey closes, Swarmia gives you a heatmap by team and an AI summary with prioritized action points, so you can see where to dig in and where to celebrate. Industry benchmarks and your own historical trends show whether the changes you make are working.

Yes. Survey responses are anonymous, and engineers can leave open comments anonymously if they want.

Yes. On the Standard and Enterprise plans, Swarmia connects survey responses with system metrics, so you can see why a number moved, not just that it did. If cycle time spikes on a team, you can check their survey answers about code review load in the same place.

A quarterly cadence works well for most engineering organizations. It’s often enough to see whether changes are working, and rare enough to avoid survey fatigue.

Swarmia automates software capitalization by measuring engineering effort from the tools engineers already use and categorizing it with rules you define. You set what counts as capitalizable using issue tracker fields like labels, custom fields, or projects, and Swarmia applies those rules as work happens.

No. Swarmia measures effort from commits, pull requests, reviews, comments, and in-progress issue activity, so engineers never fill in a timesheet or a capitalization spreadsheet. An HR system integration accounts for part-time work, vacations, and sick leave. Engineers don’t need to touch the capitalization module at all. We also support country-specific legislation like WBSO in the Netherlands, which requires engineering managers to review their teams’ hours every two weeks.

Swarmia’s FTE model has been validated against traditional time tracking, and its reports hold up in Big Four audits. It weighs each type of activity, normalizes per engineer, and adjusts for time off and inactivity.

Swarmia’s reports are built for audits: the approach is SOC 1 audited, and many of our customers have passed audits with Big Four firms. Every report has a full audit trail, from the top-level capitalization percentage down to individual issues and commits.

Yes. Finance and auditors can drill down from any capitalization percentage to the features, issues, pull requests, and commits behind it. Swarmia gives FTE breakdowns per person, per initiative, and per month, while salary data stays in finance’s own systems by design.

Many engineering intelligence platforms are strong at reporting, Swarmia is built so engineering leaders and teams can take action based on the data. Swarmia’s differentiation rests on three things: a shared definition of engineering effectiveness that connects metrics, developer sentiment, AI impact, and investment; a data model that produces insights you can trust; and feedback loops that turn those insights into action.

Vendor dashboards work for managing one tool, Swarmia puts every AI coding tool into one view, in one format, organized by your teams. Vendor data usually sits at the user or API-key level, visible to one or two admins, and each tool defines “activity” differently. Those dashboards are also built to bill you, not to help you decide what to keep and what to cut.

Building in-house can work if your platform team has time to spare, but the real question is whether maintaining it is the best use of that time. Every vendor API change, new AI tool, and reorg means more upkeep, and the hard part is trustworthy models for effort, team structure, and time off. Swarmia gives you that foundation from day one, plus an API and MCP if you want to build your own analysis on top.

A BI dashboard is a good place to start, and it gives you visibility. Swarmia adds signals, recommendations, working agreements, and notifications that make it easier to turn insights into action. Swarmia also takes care of the most difficult part, which is data modeling. Team structures, effort, and research-backed metric definitions come out of the box, so nobody has to maintain queries every time something changes.

Yes. Swarmia covers engineering metrics, developer experience surveys, AI adoption, and software capitalization on one org structure and one data model. Specialized tools can go deep in their own lane, but they don’t talk to each other, so you can’t connect a cycle time spike to survey feedback about code review. The Standard plan includes all four modules for less than buying them separately.

Swarmia doesn’t process or use your source code. It works from metadata such as pull requests, commits, reviews, and file changes. Organizations with strict policies can route the connection through a proxy agent on their own infrastructure.

Swarmia is a cloud platform, with no fully on-prem version. For tighter control, you can run Swarmia’s proxy agent on your own infrastructure to isolate the connection between your tools and Swarmia.

By default, Swarmia stores customer data in the European Union. If you require data residency in another location, please contact your account manager or email us at security@swarmia.com.

Swarmia uses OpenAI and Anthropic for AI-assisted analysis, summaries, and classifications, and neither provider is allowed to train models on your data. Swarmia doesn’t use your data, including AI inputs and outputs, to train models either. Both providers process data in the US, even though Swarmia hosts customer data in the EU by default. AI features are on by default, and you can opt out of the features that rely on these providers by emailing hello@swarmia.com. Details are on the security page.

Swarmia is SOC 2 Type 2 and SOC 1 Type 2 compliant. For a full list of security certifications, visit our security page.

Swarmia integrates with GitHub, GitLab, Jira, Linear, Slack, Microsoft Teams, HR systems, and AI coding tools including Claude Code, Codex, GitHub Copilot, and Cursor. Team structures can come from your code hosting platform, a CSV import, or the Team API. For a full list of integrations, visit our integrations page.

Getting started with Swarmia mostly means connecting tools: your code hosting platform, issue tracker, AI coding tools, and Slack or Microsoft Teams. The data will start flowing in immediately, but can take 48 hours to backfill for larger organizations. Developer experience surveys need no code hosting connection, so they’re the fastest place to start. We offer 14-day free trials as a default but are also happy to run longer, structured proofs of concept when needed.

Swarmia is priced per engineer per month, and pricing is public. You can pay monthly or annually, and annual plans cost less than the equivalent monthly plans. The Standard plan bundles all four modules, and each module is also sold on its own. Swarmia is free for companies with up to 9 developers, and billing counts the unique team members added to teams in Swarmia.