Build a clearer search workflow.
Learn how Atlas crawls modern sites, ranks technical opportunities, evaluates AI discoverability, and helps teams verify improvement.
Quickstart
Create a project, run a crawl, and find your first priority action.
About 10 minutes →02Core concepts
Understand the data model behind projects, crawls, pages, and issues.
Learn the model ↓03Prioritization
See how severity, page reach, and performance data shape the queue.
Understand priority ↓Projects, crawls, and evidence
A project is the long-lived home for one site or environment. A crawl is a timestamped observation of that project. Atlas stores page-level evidence inside each crawl so results remain reproducible and comparable.
Issues and priority
Not every valid finding deserves immediate work. Atlas separates technical severity from business priority, then layers in how many pages are affected and—when Search Console is connected—the performance of those pages.
| Signal | What it tells you |
|---|---|
| Severity | How strongly the condition can affect search behavior. |
| Reach | How broadly the condition appears across pages and templates. |
| Search impact | How much organic demand is connected to affected URLs. |
| Change state | Whether a finding is new, persistent, improved, or resolved. |
AI visibility
AI visibility starts with the same foundations as search visibility: crawler access, understandable content, stable identifiers, and reliable structured data. Atlas checks these foundations alongside crawler-specific directives.
Crawl comparison
Comparison answers a more useful question than “what is wrong?”: what changed? Select two completed crawls to isolate new issues, resolved issues, and changes to page signals after a deployment or migration.