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AI Recruitment Automation Workflow
Designed and developed an end-to-end AI-powered recruitment automation workflow using n8n to streamline the candidate screening process. The workflow automatically collects job applications, processes resumes, extracts candidate information, evaluates qualifications using AI, updates Google Sheets, and sends personalized email notifications based on the evaluation results. By integrating multiple services through APIs and intelligent decision-making, this solution significantly reduces manual effort, accelerates hiring, improves accuracy, and provides a scalable recruitment system for modern businesses. Built using n8n, AI Models (OpenAI/Gemini), Google Sheets, Google Drive, Gmail, JavaScript, HTTP Requests, and API integrations, this workflow demonstrates expertise in AI automation, workflow orchestration, and business process optimization.
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Most inbound bottlenecks aren't caused by low lead volume—they happen during triage.
When inquiries roll into a Google Sheet or CRM, operations teams often waste 10–15 minutes per submission reading through messy paragraphs, deciphering budget mismatch, and manually deciding who gets an immediate call vs. a standard rate sheet.
Instead of adding a bulky CRM add-on, I documented a lightweight 3-step automation pipeline built inside Make:
Intake & Extraction: An active listener triggers immediately upon a new submission, extracting core variables: client scope, target deliverables, timeline, and stated budget.
Context-Aware Evaluation (Gemini 2.5 Flash): The payload passes through an AI evaluation node with strict guardrails:
Evaluates budget against minimum agency criteria.
Assigns a triage score: Hot (immediate priority), Warm (nurture), or Cold (disqualified/template reply).
Generates a strict 15-word operational summary—no long paragraphs.
Determines an automated next step (e.g., routing to an account lead or flagging for asynchronous follow-up).
Data Return & Clean Pipeline: Appends the structured classification directly back to the master operational tracker, keeping the sheet filterable and clean.
The outcome: The sales and operations team can filter the entire board by priority status in two clicks, cutting first-touch response time to minutes without manually reading every single submission.
I’ve documented the full scenario map, execution logic, and data schemas below.
Curious how other agency operators and automation leads here handle their lead enrichment layer—are you doing AI scoring at the form level, or later in the CRM pipeline?:
For the budget gate, I'd keep an unstated budget separate from one explicitly below your minimum. Does the Make route ask for clarification when the amount or currency is missing, so a potentially suitable lead doesn't fall into Cold by default?
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.
I'd test calm messages about a service outage alongside angry messages about a routine request, so sentiment doesn't become a proxy for urgency. When the model is unsure of the department or priority, does the email go to a human review queue rather than being silently assigned?
🚀 ST Automation Cloud - Enterprise AI Automation SaaS
What it does:
ST Automation Cloud is a next-generation platform that connects your daily business tools (Gmail, Google Sheets, Slack, Discord, Webhooks) into one unified workspace. Powered by Gemini AI, it allows users to build visual, multi-step automation workflows without writing a single line of code. It handles everything from data syncing to executing complex, autonomous AI pipelines.
How it is profitable (Business Value):
Massive Time & Cost Savings: By automating repetitive tasks (like lead generation, email sorting, and data entry), it saves hundreds of man-hours, directly reducing operational costs.
Zero Human Error: Automated workflows ensure 100% accuracy in data transfer between different apps, eliminating costly manual mistakes.
Infinite Scalability: Businesses can scale their operations 10x without needing to hire more staff. The autonomous AI agents work 24/7 in the background.
High-Throughput ROI: With enterprise-grade security and a premium user interface, it provides a quick return on investment by streamlining critical pipelines.
In short: It transforms manual, time-consuming operations into a fast, reliable, and fully automated digital workforce.
I'd distinguish a completed action from a completed workflow in the run history. If Gmail sends successfully but the next Slack step fails, can a user resume from Slack without sending the email again?