This intelligent automation platform reduced customer support costs significantly, cut average response times from several hours to seconds, and created a scalable foundation for future AI-assisted operations.
Seamless Automation of Customer Queries
n8n served as the central nervous system for orchestrating the flow of data between AI models, legacy databases, APIs, and customer-facing communication channels.
I leveraged n8n’s low-code environment and node-based architecture to build a series of modular, reusable workflows that managed everything from natural language input parsing to SQL query execution, error handling, and intelligent escalation.
Reduced Costs While Improving Customer Experience
By offloading repetitive and data-driven questions to AI workflows, the existing human team was freed up to focus exclusively on edge cases and higher-value interactions. This not only reduced labor costs but also resulted in faster response times and a smoother, more consistent customer experience across all channels.
This intelligent automation platform reduced customer support costs significantly, cut average response times from several hours to seconds, and created a scalable foundation for future AI-assisted operations.
-
Visual Workflow Design: Allowed rapid iteration and testing of complex logic without traditional code deployment cycles.
-
Native OpenAI and DB Integration: Simplified connection to both LLM APIs and structured data sources in a single tool.
-
Flexible Error Handling: Added retry loops, conditional branches, and alerting for edge cases and critical paths.
-
Contextual Query Building: Used function and merge nodes to dynamically assemble safe queries based on prior conversation memory.
-
Composable Architecture: Created modular sub-workflows for tasks like transcription handling, sentiment analysis, and escalation, improving maintainability.