Email Triage Automation
The Challenge
Growing companies often struggle with overflowing shared inboxes (sales@, support@, info@). Manual sorting, categorizing, and assigning emails to different departments causes response delays. Even worse, high-priority issues—such as urgent billing complaints or system failures—frequently get buried in the noise, leading to missed deadlines and unhappy clients.
The Solution & Architecture
I engineered an enterprise-grade inbox management and automation architecture using n8n, Gmail API, and OpenAI.
The system workflow functions as follows:
Ingestion & AI Classification: The workflow triggers instantly upon receiving a new message (Gmail Trigger), sanitizes the payload, and passes the text to an OpenAI Chat Model for sentiment analysis and intent classification.
Smart Categorization & Labeling: Based on the AI's output, a routing node assigns the email to the correct department (Finance, Sales, Technical Support, Partnerships) and automatically applies matching Gmail labels in real time.
Priority Escalation Routing: If the system flags an email as high-priority, it immediately triggers a secondary logic line. This packages the case details and shoots an urgent alert card directly into a dedicated Discord channel, complete with a summary and recommended actions.
AI-Assisted Contextual Response: Simultaneously, the system evaluates if an instant acknowledgement is needed, generates a contextual, brand-aligned draft reply using LLMs, and sends it directly within the original Gmail thread to reassure the client.
Business Results
Zero Sorting Overhead: Fully eliminated the manual labor required to filter, read, and forward inbound corporate emails.
Accelerated Escalation: Critical, high-priority issues (like duplicate billing charges) are delivered to managers' chat screens within seconds.
Improved Client Retention: Automated contextual auto-replies ensure clients receive an immediate confirmation that their issue is prioritized and routed to the correct desk.
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AI Support Agent
The Challenge
E-commerce stores and digital platforms lose revenue when customer support is slow, especially during nights and weekends. Hiring full-time support teams for routine questions (FAQs) and simple order tracking is expensive. The business required an intelligent AI support agent capable of checking order data via APIs, answering company-specific questions, and accurately escalating complex customer complaints to a human team without losing context.
The Solution & Architecture
I engineered an advanced, contextual AI Support Agent using n8n as the central orchestrator and LangChain-based routing logic.
The technical infrastructure includes:
Advanced AI Orchestration: Inbound customer chats are processed by an OpenAI Support Model paired with a Chat Memory node to maintain full conversation context across multiple messages.
Tool Calling & API Integrations: The AI agent is equipped with native tools—a FAQ Knowledge Tool to answer company rules and a dynamic Order Status API Tool that sends live REST API (GET) requests to fetch real-time shipping data.
Smart Human-Handoff Protocol: If a customer reports a damaged item or explicitly requests a human, a conditional routing node shifts the flow. It generates a structured handover file and pushes an urgent notification to the team via Discord, including the customer's intent and order ID.
Isolated Incident Catching: A dedicated Error Monitoring workflow listens for third-party API exceptions, instantly mapping failures and routing technical diagnostic details to Discord to prevent silent drops.
Business Results
Instant First-Line Support: Automated 70%+ of standard FAQ and order lookup inquiries, cutting response times to milliseconds.
Flawless Escalation: High-priority support cases (like damaged orders) are summarized by AI and pushed to humans in under 2 seconds.
Production Stability: Technical teams are alerted immediately if an API dependency fails, ensuring maximum system uptime.
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Weekly KPI Report
The Challenge
Marketing teams and executives waste hours every single week logging into different dashboards, manually compiling cross-channel performance metrics (Revenue, Spend, ROAS), and writing data summaries. Crucial performance anomalies or drops in campaign efficiency are often missed due to human oversight, and report generation is frequently delayed.
The Solution & Architecture
I engineered a fully autonomous analytics and reporting engine powered by n8n and OpenAI that turns raw data into formatted, insightful management reports completely on autopilot.
The technical workflow features:
Data Fetching & Calculation: The flow initiates via a cron schedule (Weekly Report Schedule), validates inbound data payloads, and executes custom JavaScript logic to calculate core marketing KPIs across different channels.
AI-Powered Insights Generation: Calculated metrics are instantly pushed to a Weekly KPI Analyst Model (OpenAI GPT). The model conducts deep data analysis, evaluates campaign efficiency, highlights top channels, and generates actionable, strategic recommendations for budget reallocation.
HTML Report Engineering: The structured AI response and aggregated tables are dynamically compiled into a clean, beautiful, native HTML dashboard report file.
Multi-Channel Delivery & Stability: The pipeline automatically posts a rich text breakdown along with the attached HTML report directly to the team's Discord channel. A secondary, dedicated Error Monitoring workflow immediately triggers high-priority alerts to developers if any data node fails.
Business Results
Hours Saved: Eliminated 100% of the manual labor required to compile weekly cross-channel marketing reports.
Instant Strategic Decisions: Management receives immediate, high-fidelity AI recommendations on ad spending optimizations directly in their chat app.
Zero Silent Crashes: The system is protected by an isolated error-handling flow (KPI Report Error Trigger), ensuring bulletproof technical execution and data delivery.
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The Challenge
When a new client signs a contract or makes a payment, the onboarding process is often slow and manual. Account managers waste valuable time creating cloud storage folders, setting up database records, sending out standardized welcome packages via email, and manually slacking the team. Delays in this initial setup hurt the client experience right from day one.
The Solution & Architecture
I engineered a fully autonomous client onboarding pipeline using n8n that links operational databases, storage systems, and notification systems into a seamless 1-second workflow.
The system architecture includes:
Data Processing & Storage: The workflow securely intercepts client data (Receive New Client), validates parameters, and automatically updates the central system database.
Dynamic Resource Provisioning: The automated flow directly calls the Google Drive API to instantly spin up a dedicated client folder with appropriate permissions (Create Client Folder).
Multi-Channel Communications: The pipeline triggers Gmail to fire off a personalized welcome onboarding message, updates the database logs, and routes a highly detailed summary card to the internal team via a custom Telegram Bot.
Enterprise-Grade Error Handling: Built-in error catching lines intercept failures at every critical junction (Drive, Gmail, Telegram) to ensure operational failures never go unnoticed.
Business Results
Instant Activation: Reduced client onboarding and file-structure creation times from 30+ minutes down to less than 2 seconds.
Unified Visibility: Internal teams receive instantaneous, highly descriptive updates via Telegram with direct cloud folder links.
Flawless Delivery: Eliminated human data-entry errors, ensuring every single client receives identical, prompt, and premium treatment immediately upon conversion.
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