> For the complete documentation index, see [llms.txt](https://help.swarmia.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.swarmia.com/features/swarmia-ai.md).
# 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](https://help.swarmia.com/features/metrics/explore) 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](https://www.swarmia.com/build/) 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](https://www.swarmia.com/changelog/2026-04-02-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 .
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://help.swarmia.com/features/swarmia-ai.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.