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Most lead generation tools collect leads.
Mine scores them, analyzes them, and logs them automatically.
I built an AI Lead Intelligence Engine using n8n that triggers the moment a form is submitted. It normalizes the data, runs it through an AI scoring model, detects industry and buying intent using Gemini, assigns a HOT/WARM/COLD tier, and saves everything to a live CRM sheet.
Built for businesses that are tired of chasing cold leads manually.
This is Stage 1. Stage 2 adds automated personalized outreach. Stage 3 adds an AI voice call within 60 seconds.
If you run a business and lose leads because follow-up is slow, this system fixes that.
Before those HOT/WARM/COLD tiers trigger outreach, I'd check them against leads reviewed by the sales team, especially good prospects labeled COLD. Do you save the scoring reasons in the CRM sheet so the team can spot and correct misclassifications?
Great point Kapil. Yes, the “Score Signals” column in the CRM sheet logs exactly why each lead got their score (e.g. “Has company, Provided phone, LinkedIn source”). So misclassifications are visible and correctable.
That said, you’re right that COLD labels especially need a...
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What if every new lead could be handled before you even open your inbox? ⚡
This AI-powered workflow turns a new email inquiry into a structured, ready-to-handle lead — automatically.
A new inquiry arrives → AI extracts the important details → Airtable/CRM is updated → the response goes through optional human approval → a personalized email is sent → Notion is updated → the team gets notified in Slack → performance data is collected for reporting.
The goal isn't to remove people from the process. It's to remove the repetitive work around them.
This type of workflow can be customized for B2B companies, SaaS businesses, agencies, real estate, e-commerce, recruitment, consulting, customer support, healthcare, finance, education, and other service businesses.
Already know what you want to automate? → Send me your current workflow and I’ll map out how we can automate it.
Still doing repetitive work manually? → Tell me the task that consumes your team’s time, and I’ll help identify what can be automated.
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I'd use the human approval step to capture corrections, not just a yes/no decision. If a reviewer changes the extracted lead details, does the workflow update Airtable and the reporting record before sending the email?
Automated LinkedIn Hiring Signal & AI Outbound Engine
Overview:
Designed and deployed an autonomous outbound lead generation system using n8n. The workflow captures hiring intent signals from LinkedIn, identifies relevant executive buyers, enriches verified contact data, and drafts contextualized sales copy through an integrated LLM.
Tech Stack:
n8n • Apify • SearchLeads API • OpenRouter (Nemotron LLM) • Google Sheets API • Telegram Bot API • JavaScript
Core Deliverables:
Automated Signal Scraping: Continuous monitoring of fresh job posts across target industries.
Granular Data Filtering: Exclusion logic for staffing agencies, company headcounts over 250, and unverified domains.
Multi-Source Enrichment: Automated discovery of decision-makers (C-Level, VP, Director) with validated work emails.
Context-Aware Email Generation: Custom prompting architecture that maps the open role's requirements directly into a tailored value proposition.
Data Synchronization & Alerts: Bi-directional sync with Google Sheets and real-time push alerts via Telegram.
Impact:
Replaces 10+ hours of weekly manual SDR prospecting with a continuous background process that delivers high-intent, enriched leads directly to the sales inbox.
I built an AI voice ordering workflow to help a restaurant capture customer orders and pass them to the kitchen with less manual work.
Using Vapi, I configured a voice assistant with the restaurant’s menu and prices to collect customer details and orders. After each call, a webhook triggers an n8n workflow, where OpenAI extracts the order into structured data. The workflow then notifies the kitchen and logs the order in Google Sheets.
I handled the voice assistant setup, webhook integration, AI prompts, and workflow implementation. The solution reduced manual order entry and made order information easier for the kitchen to access.
Tools: Vapi, n8n, OpenAI, Google Sheets, and webhooks.
Having the assistant feed orders straight into the kitchen cuts the manual handoff. The call transcript in Sheets also gives a clear audit trail.