This AI agent continuously monitors brand mentions across Twitter/X, Reddit, and News, analyzes sentiment and trends, and automatically notifies Slack, leadership, and Jira for rapid crisis containment.
The AI agent continuously monitors brand mentions across Twitter/X, Reddit, and News sites, normalizing data into a unified structure. It then analyzes sentiment, amplification factors, and 24-hour baselines to identify crisis signals. When a crisis is detected, it automates alerts, executive briefs, and issue tracking to enable fast containment.
Monitors multiple platforms, analyzes sentiment, and routes crisis responses.
Ingests mentions from Twitter/X, Reddit, and News API
Normalizes data into a unified schema
Filters duplicates and previously analyzed items
Analyzes sentiment and amplification factors for each mention
Detects trend shifts against 24-hour baselines
Classifies crises by severity and triggers automated responses
This AI agent reduces risk by turning scattered mentions into immediate, actionable steps during a crisis. Before, teams faced fragmented data, slow detection, and ad-hoc escalation. after, teams enjoy centralized monitoring, rapid crisis detection, automated routing, executive briefs, and formalized tracking.
A simple 3-step flow for non-technical users.
Collects brand mentions from Twitter/X, Reddit, and News API every 10 minutes and normalizes them into a unified schema.
Runs AI sentiment analysis, extracts amplification factors, and compares current sentiment to a 24-hour baseline.
If a crisis is detected, classifies severity, triggers alerts to Slack and leadership, creates a Jira ticket, and logs the event; otherwise logs for trend analysis.
A realistic scenario showing monitoring, detection, and response.
Scenario: A product outage triggers a spike in negative mentions on Twitter/X and Reddit. Within 20 minutes, the AI agent detects a sharp sentiment drop and a 35% increase in mentions. It classifies the crisis as HIGH, generates an executive brief, posts a Slack alert to the crisis channel, emails leadership with the brief, creates a Jira ticket, and logs the event for post-crisis analysis.
Roles that gain real-time crisis visibility and automated routing.
Needs real-time brand sentiment context across platforms to steer messaging.
Requires immediate alerts and recommended actions for crisis comms.
Benefits from a structured escalation workflow and tracked actions.
Wants high-level briefs and timely decisions during a crisis.
Needs early indicators to manage customer impact and queue shifts.
Sees auditable logs and regulated response processes.
Tools the agent uses to gather data and deliver responses.
Ingests mentions every 10 minutes and serves as the primary data source.
Ingests discussions and mentions for sentiment across communities.
Fetches brand mentions from news outlets and blogs for breadth.
Sends crisis alerts to the crisis channel and posts executive briefs.
Dispatches leadership briefs and updates via SMTP.
Creates and tracks crisis-related tickets for action owners.
Key scenarios where this AI agent adds concrete value.
Common concerns and detailed explanations.
Crisis signals are computed in near real-time as mentions stream in every 10 minutes. The AI agent compares sentiment and amplification against a 24-hour baseline to flag significant shifts. Severity is categorized automatically, and if thresholds are exceeded, alerts and tickets are generated within minutes. Users can tune sensitivity to balance false positives and timely notification. The AI agent maintains a complete audit trail for after-action reviews.
The agent monitors Twitter/X, Reddit, and News; additional sources can be integrated via standard APIs. Each new source is normalized to the same data model to preserve consistency. You can extend monitoring to other social channels by configuring queries and connection credentials. The system supports scalable ingestion without compromising performance.
An executive brief is generated detailing the current situation, recommended actions, and owners. Slack alerts are sent to the crisis channel, and leadership receives an email with the brief. A Jira ticket is created for task tracking, and all events are logged for future analysis. The AI agent is designed to activate within minutes of detection.
Yes. The agent supports adjustable crisis thresholds and sentiment dictionaries. You can tune amplification factors and review a sample of flagged items to refine the model. Ongoing monitoring helps balance sensitivity with specificity, and you can disable alerts for known safe phrases. The system also logs all decisions for auditing and improvement.
A manual test mode lets you run the agent with test data to validate routing and content without affecting live channels. You can simulate crises of varying severity and review alert paths. The test mode records outcomes for comparison with real runs. Use the dry-run to calibrate thresholds before activation.
Alerts are delivered via Slack, email, and Jira. The crisis channel in Slack shows the executive brief and action items. Leadership emails include a concise brief and recommended actions, while Jira tickets track responsibilities and timelines. Alerts are routed to the appropriate teams based on configured channels and roles.
All mentions are stored with timestamps and source identifiers. The AI agent logs every decision, including sentiment scores and threshold reasons, to support accountability and regulatory compliance. Access controls govern who can view sensitive data and critical alerts. Regular audits can be produced from the logs for governance.
This AI agent continuously monitors brand mentions across Twitter/X, Reddit, and News, analyzes sentiment and trends, and automatically notifies Slack, leadership, and Jira for rapid crisis containment.
