Monitors public platforms hourly for brand mentions, analyzes risk with AI, and automatically notifies teams via Google Chat while creating urgent tasks in Asana.
The Brand Reputation AI Agent continuously scans Reddit, Glassdoor, and review sites via SerpAPI to surface brand mentions. It analyzes sentiment and crisis risk with Azure OpenAI to identify urgency. For high-risk issues, it triggers real-time alerts and auto-creates prioritized Asana tasks to coordinate a fast response.
Automates detection, scoring, and action for brand-reputation events.
Ingests mentions from Reddit, Glassdoor, and review sites via SerpAPI.
Analyzes sentiment and crisis risk with Azure OpenAI.
Classifies risk level and urgency for each mention.
Filters to retain only high-risk threats for action.
Triggers real-time Google Chat alerts with context.
Creates prioritized Asana tasks with ownership and due dates.
Before: manual monitoring across Reddit, Glassdoor, and review sites; delayed crisis detection; fragmented alerts; inconsistent data; slow response. After: instant high-risk alerts; centralized triage with clear ownership; faster containment; consistent evidence for decisions; streamlined cross-team collaboration.
A simple 3-step AI agent flow that non-technical teams can follow.
Collects mentions from SerpAPI across Reddit, Glassdoor, and review sites and compiles structured data.
Applies Azure OpenAI to analyze sentiment and determine crisis risk and urgency.
Sends Google Chat alerts for high-risk items and creates prioritized Asana tasks with context.
A realistic scenario showing time and outcomes.
Scenario: A SaaS brand launches a feature. Within 60 minutes, AI detects rising negative sentiment on Reddit and Glassdoor mentions. It rates the risk as high, sends a real-time Google Chat alert with links and context, and creates a priority Asana task for PR and support teams with owner and due date. The team uses the alert and task to coordinate a rapid, synchronized response across channels and resolve the issue efficiently.
Key roles that gain fast, actionable reputational insights.
Detect and triage online mentions quickly to protect brand reputation.
Coordinate crisis response with timely alerts and tasks.
Prepare proactive communications based on early signals.
Automate task creation and assignment to speed containment.
Identify sentiment shifts that affect campaigns.
Manage multiple clients with centralized monitoring and alerts.
Seamless connections that enable real-time actions inside your tools.
Searches Reddit, Glassdoor, and review sites for brand mentions using Google AI Mode.
Performs sentiment analysis and crisis risk scoring on collected mentions.
Delivers real-time alerts to designated channels when high-risk issues are detected.
Creates and assigns crisis response tasks with context and due dates.
Six practical scenarios that show concrete outcomes.
Practical, real-world concerns with detailed answers.
Alerts are delivered in real time or within seconds of a high-risk inference, depending on API response times. The system continuously streams mentions and evaluates risk against pre-defined thresholds. Network latency and API rate limits can influence timing, but the architecture supports near-instant notification for critical events. In practice, teams often see alerts within a minute of a notable spike, allowing rapid triage.
The agent scans Reddit, Glassdoor, and public review sites via SerpAPI. The integration focuses on platforms where user sentiment and reviews are most likely to indicate reputational risk. It is designed to be extended to additional sources with minimal configuration. Data from these sources is structured, timestamped, and linked to brand keywords to maintain traceability.
Yes. Risk scoring is configurable via thresholds and weighting for sentiment, volume, and velocity of mentions. You can tailor these to your brand, market, and crisis playbooks. Custom thresholds help reduce noise and prioritize true threats. The scoring model can be retrained or calibrated as brand risk tolerance evolves.
If the AI output is malformed, the system falls back to structured fallback rules and logging. It retries data processing with a safe default and notifies the operators of data quality issues. There are validation checks before alerts are sent or tasks created. Incomplete results are flagged and quarantined for human review to prevent misdirection.
Integrations use OAuth2-based authentication and role-based access controls. Data is transmitted over secure channels with encryption at rest and in transit. Access controls limit what data is visible in chats and tasks. Audit logs help track who created alerts and tasks, supporting compliance and incident review.
Yes. The agent supports multi-brand deployment with isolated configurations per brand. Each brand has independent mentions sources, risk thresholds, and notification settings. Centralized dashboards provide a consolidated view while preserving data separation. Scaling across clients is designed to be seamless and auditable.
The system logs mention metadata (time, source), risk scores, alert events, and created tasks. Logs include actions taken and the users involved in approvals or edits. Data retention aligns with policy and regulatory requirements, with options to export for further analysis. Logs support incident post-mortems and performance reviews.
Monitors public platforms hourly for brand mentions, analyzes risk with AI, and automatically notifies teams via Google Chat while creating urgent tasks in Asana.
