Swarmia AI

Swarmia AI lets you ask questions about your engineering data in plain language. Responses can include summaries, tables, charts, and next steps. You can ask follow-up questions, adjust what's shown, and open results in the Explore view to save them for later.

Getting started

Two ways to start a conversation:

1. Click Swarmia AI in the main navigation to open a new chat.

2. Click Ask Swarmia AI from any supported view — Code metrics, Issue metrics, AI adoption, AI impact, Coding agents, or Surveys.

Starting from a specific view includes that view's context automatically, so you can ask targeted questions about the data in front of you.

Asking questions

Type your question in plain language. More specific questions get better answers. For example:

• "Summarize our latest survey results and suggest next steps"

• "Why did technical debt increase for the platform team last month?"

• "How are code reviews distributed across the team this quarter?"

• "What's the average PR cycle time per team this month, and which teams are the highest?"

• "How has GitHub Copilot adoption changed over the past 3 months?"

Swarmia AI can analyze both quantitative metrics and qualitative feedback (such as survey comments). It draws on the Build book where relevant, and can suggest next steps alongside its analysis.

Response format and follow-ups

Responses can include:

• Summaries — plain-language analysis and recommendations

• Tables — breakdowns by team, person, time period, or metric

• Charts — trends and comparisons visualized

After each response, you can:

• Ask follow-up questions to go deeper

• Request a different breakdown (e.g., by team, by author, by time period)

• Add or remove data from a chart

• Open results in the Explore view to tweak, save and revisit them

By default, Swarmia AI responds quickly. You can increase the reasoning level to get more detailed analysis — this may take a bit longer.

Saving results

Any table or chart in a response can be opened in the Explore view, where you can save it as a custom report to revisit later.

Limitations and approprate use

Results depend on available data — missing or inconsistent data can affect accuracy.

Swarmia AI identifies patterns in engineering activity. It doesn't measure individual productivity, performance, or competence, and its outputs can be incomplete or wrong. Activity counts (such as PRs opened or merged) vary widely with project type, review load, batch size, and role, and do not indicate how well or how much a person contributed.

Don't use Swarmia AI outputs — including any per-person metric, ranking, or comparison — as a basis for decisions about individuals, such as performance reviews, compensation, promotion, discipline, or termination. These outputs aren't designed or validated for that purpose. Use them for team- and system-level insight, and apply your own judgment with full context.

Every AI-generated insight is backed by an explicit data query. Click Explore to see exactly what was asked, adjust if needed, and rerun it any time.

Sharing feedback

Rate each response with 👍 or 👎. For more detailed feedback, reach out to your customer success manager or email [e-mail].