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LeadOps Pipeline & AI Analytics
Goal: Automate lead qualification, scale QA coverage from 15% to 100%, and eliminate 3 hours of manual weekly reporting.
Solution: Designed a multi-agent n8n architecture with autonomous tool-calling and Redis memory. Built 3 AI personas: an empathetic Sales Agent capturing Zoho CRM leads, a strict QA Inspector analyzing chat histories into Google Sheets, and a Monitoring Agent delivering Telegram summaries.
Impact: Saved 45+ team hours monthly. Increased conversions by 35% via 2-second AI responses. Cut reporting time from 3 hours to under 1 minute.
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🚀 Automated Lead Management System
I built an automated lead management workflow using n8n that captures incoming leads, stores them in Google Sheets, and instantly notifies the sales team on Telegram.
Capture → Enrich → Score → Save → Notify
Built to reduce manual work, improve response time, and prevent missed leads.
#AI #Automation #n8n #CRM #LeadManagement
Nice work sir,
Sir we can Build this normally with App script. I just Built yesterday.
Where Google sheet will received the leads from any channel + store and distribute as per described assignment rules and notify with lead details to respected person.
What if your PC could actually listen, understand, and do the work for you?
I’m building that idea into something real.
Meet AURA — my personal AI voice assistant for Windows.
Instead of building another chatbot that only answers questions, I’m experimenting with an AI agent that can actually interact with my computer and help with everyday work.
So far, AURA can:
• Have live voice conversations
• Convert speech to text and respond with voice
• Open applications like Excel, Power BI, Chrome, and Windows Settings
• Search the web and YouTube through voice
• Perform basic PC and file operations
• Understand requests through Gemini
• Execute actions through a safety-controlled automation layer
• Continue listening after completing a task
But this is only the beginning.
My long-term goal is to make AURA understand my actual workspace — including what’s happening on my screen and inside applications — so I can simply say:
“Open my Excel file, check the sales data, clean the date column, and add a formula for total revenue.”
And let AURA handle the workflow.
I also want it to become useful for my own Data Analytics work — from Excel and Power BI workflows to repetitive desktop tasks, research, and automation.
I’m building AURA with Python, AI, voice technologies, desktop automation, Excel, Power BI, and LLMs, while keeping safety and human control at the core.
It’s still far from the final vision.
But that’s exactly what makes the project interesting.
I’m not just learning how AI agents work.
I’m trying to build one that I can actually use every day.
Building in public. Learning by building. 🚀
#AI #AIAgents #Python #AIAssistant #VoiceAI #DesktopAutomation #DataAnalytics #PowerBI #Excel #Automation #BuildInPublic
The screen-reading step is where I would put the guardrail. Once AURA can read what is in the window, everything on that screen is input - and a page it opened from a voice search can hold a sentence written to be read as an instruction. I spent a while trying to rob my own...
Cold Email Campaign Lead Generation Results
I worked on a targeted B2B cold email campaign focused on reaching relevant prospects and generating qualified business opportunities.
My role included lead generation, ICP-based prospect research, data preparation, and cold email outreach to ensure the campaign reached the right audience.
Campaign Results
14.5K+ emails sent
49.2% open rate
4.9% reply rate
50 opportunities generated
$760K reported opportunity value
The campaign generated consistent engagement and helped turn targeted cold outreach into 50 potential business opportunities.
Services: Lead Generation · Cold Email Marketing · B2B Prospect Research · ICP Targeting · Data Enrichment · Email Outreach
50 opportunities from 14.5K sends is a strong conversion path. Great proof that cold email isn't dead, it's just usually done wrong.