Autonomous Google Reputation Engine: Agentic

Autonomous Google Reputation Engine: Agentic Review Filtering & Human-in-the-Loop Approval

The Objective: To protect brand equity and automate reputation management by instantly intercepting, analyzing, and resolving negative Google reviews through a highly controlled AI triage system.

The Solution: Architected a sophisticated, multi-stage agentic workflow that continuously monitors a Google Business Profile. When a negative review is detected, the system triggers an intelligent processing chain. Instead of blindly publishing an automated response, the system utilizes a custom Google Gemini AI node to analyze the sentiment and draft a highly contextualized, empathetic reply. It then pauses the workflow and routes an immediate approval request directly to the business owner via messaging integration (e.g., Slack or SMS). Once the owner reviews and approves the drafted message with a single click, the system dynamically pushes the final response back to Google to resolve the dispute.

Core Capabilities & Tech Highlights:

Negative Review Interception: Autonomous detection of sub-4-star or critical feedback to immediately trigger reputation-safeguard protocols without manual monitoring.

Human-in-the-Loop (HITL) Automation: Implements an enterprise-grade approval loop, ensuring the business owner maintains absolute control before any external communication is finalized.

Context-Aware LLM Response Generation: Utilizes Google Gemini API architectures to evaluate customer sentiment and generate professional, brand-aligned de-escalation responses.

Dynamic Notification Webhooks: Leverages secure data backends (like Airtable) and custom HTTP POST requests to sync review status, push interactive approval messages to the owner, and execute the final deployment.

The Impact: Replaced stressful, manual public relations tasks with a 24/7 automated brand safeguard that protects local search rankings while maintaining complete executive control over customer communications.