AuraFlow Operations Engine
A unified AI operations platform that automates customer support, order management, and inventory alerts — handling 70% of support tickets without human intervention.
Project Overview
AuraFlow was designed for a fast-growing e-commerce brand that had outgrown its support team. With order volumes doubling quarter over quarter, their customer service queue was overwhelmed — average response times had ballooned to 18 hours, and repetitive queries about order status, returns, and sizing consumed the majority of agent time.
We built an intelligent operations engine that unifies customer support automation, order lifecycle management, and proactive inventory alerting into a single platform. The system handles routine interactions autonomously while seamlessly escalating complex cases to human agents with full context.
Technical Architecture
The conversational AI layer combines Dialogflow for intent recognition with the OpenAI API for natural language generation. Dialogflow handles structured intents — order lookups, return initiation, sizing guides — with deterministic accuracy, while GPT-powered responses handle open-ended queries with a brand-consistent tone trained on 10,000 historical support conversations.
The backend is built with Node.js and TypeScript, providing type-safe API endpoints that integrate with the client's Shopify store, shipping providers, and warehouse management system. Redis serves as both a session cache for active conversations and a real-time pub/sub layer for inventory alerts.
Workflow automation spans three platforms: n8n handles complex multi-step processes like return authorisations and refund approvals, Make manages data synchronisation between the e-commerce platform and internal tools, and Zapier connects lightweight triggers like review requests and post-purchase follow-ups.
The operations dashboard is a Next.js application styled with Tailwind CSS, giving the support team real-time visibility into automated resolutions, escalation queues, and customer sentiment trends. All conversation and order data is stored in PostgreSQL with row-level security for multi-team access.
The entire platform runs on Google Cloud with Docker containers orchestrated by Kubernetes, providing auto-scaling during flash sales and Black Friday traffic spikes. Health checks and alerting ensure the system maintains sub-second response times even under peak load.