Ask anything about your crawl.

Crawl-aware context. Every answer is grounded in your actual crawl — page count, structure, extracted data, detected issues, and embeddings. Not generic web knowledge.

Natural language queries. Ask anything: "Which pages have high word count but no meta description?" The agent handles the filtering logic so you don't have to.

Complex multi-step filtering. Combine conditions that would take hours to set up manually. Chain filters, cross-reference data points, and isolate specific page subsets in one conversational request.

Pattern recognition. Surface patterns that aren't obvious from individual page data — templating issues, structural problems, topical gaps, and anomalies across large page sets.

Issue spotting and explanation. Ask the agent to explain a finding, walk through its impact, and suggest a practical fix given your site's structure. Context-aware, not generic.

Data summarization. Get a plain-English summary of any crawl, filtered view, or issue set — useful for briefing a client or handing off findings to a developer.

Follow-up reasoning. The agent builds on context across the conversation. Ask follow-ups, refine, and dig into specifics — more like talking to an expert than running a query.

Launch directly into action. From any agent response, kick off a workflow, open the filtered page table, or feed the result directly into an audit document.