Real-time monitoring of X posts with automatic categorization and JSON output.
The AI agent authenticates to X using your Airtop profile, opens the specified search URL, and scrolls to load fresh posts. It extracts up to 10 English-language posts, filters for relevance, and labels each with a category or [NA]. It returns a JSON array ready for ingestion in engagement, research, or competitive analysis.
Executes live post monitoring, categorization, and structured output.
Log into X with the Airtop profile.
Open the provided search URL.
Scroll through results to load posts.
Extract up to 10 valid English posts.
Filter and classify each post by category or [NA].
Return the structured results as JSON.
Before → 5 real pain points. After → 5 clear outcomes.
A simple 3-step flow for non-technical teams.
Accepts Airtop profile, x_url, and relevant categories, then initializes a browser session.
Opens the search URL and scrolls through results to load posts.
Extracts up to 10 English posts, labels each with a category or [NA], filters out [NA], and returns a JSON array.
A realistic setup showing inputs and outcomes.
Scenario: A marketing team sets up the AI Agent to monitor the live X search for 'ai agents' for 5 minutes using an Airtop profile. It extracts up to 10 posts, categorizes them into predefined topics, and returns a JSON array to feed into the engagement dashboard. Time to run: ~5 minutes. Outcome: a ready-to-ingest JSON payload with 10 categorized posts.
Roles that gain real-time social post insights.
Needs real-time post data to inform campaigns and measure topical relevance.
Requires timely posts for engagement opportunities.
Watches for mentions and sentiment around the brand.
Tracks competitors' conversations and positioning.
Identifies posts that indicate buying intent or collaboration potential.
Gathers user feedback from live conversations for quick iteration.
Tools that enable automation and routing.
Authenticates and drives browser automation (X login, URL navigation, scrolling).
Outlines flows and routes results to downstream workflows and data stores.
Delivers classified posts or alerts to channels for review and action.
Six practical workflows that benefit from real-time post insights.
Common questions about operation and data.
The JSON array includes writer, time, text, url, and category for up to 10 English posts. Each item is labeled with a category or [NA] if not relevant. The structure is designed for easy ingestion by downstream automation or analytics. If you need additional fields, you can extend the classifier to include sentiment or entity mentions in future runs.
Up to 10 posts are extracted per run, filtered for English language. Posts that do not meet basic relevance criteria can be pruned. The agent discards non-matching results and returns only the relevant subset as a JSON array.
Yes. The AI agent uses your Airtop profile to authenticate to X before performing searches. This ensures access to live results and preserves session context for consistent scraping. Credentials are used only for the automated session and are not stored long-term by the agent.
Yes. The agent accepts a user-defined list of categories. You can adjust the taxonomy to match your research topics, campaigns, or seed keywords. Classification is performed against the provided category set, with non-matching posts labeled as [NA].
The agent filters for English-language posts. Non-English posts are skipped to ensure consistent parsing and categorization. If you need multilingual support, consider extending the classifier with language detection and translation steps.
The AI agent runs within your authenticated Airtop session and does not store credentials beyond the active run. Data handling is limited to the necessary extraction and JSON output. You control the inputs (profile, URL, categories) and can terminate the session after each run to minimize exposure.
Yes. The agent is designed to be triggered by other workflows (for example, a community engagement pipeline). You can schedule periodic runs or invoke it on-demand. Each run is a self-contained extraction and classification that produces a ready-to-use JSON payload.
Real-time monitoring of X posts with automatic categorization and JSON output.
