Muhammad Aatir

Problem: Patients often didn't know which specialist to consult and had to manually call clinics to book appointments.

Solution: Built an AI system that analyzes symptoms, recommends the right specialist, and books appointments through a voice-based calling agent.

Result: Reduced manual front-desk workload and helped patients reach the right care faster.

Problem: Real estate acquisition deals were being lost to slow, manual follow-up between the first seller call and a signed contract.

Solution: Built an AI voice agent (Vapi) that qualifies sellers and calculates real-time cash offers, feeding an n8n workflow that updates GoHighLevel with zero manual data entry.

Result: GHL auto-generates and routes purchase agreements for e-signature within minutes of the call ending.

Problem: Manual inbox triage, including reviewing image-based damage complaints, consumed hours daily.

Solution: Built an automation that fetches Gmail emails, uses GPT Vision to analyze product images, and drafts context-aware replies from full conversation history.

Result: Cut manual inbox management from hours to minutes using n8n, GPT-4o, Gmail API, and Vision AI.

Problem: Sales teams manually cold-called leads for insurance outreach, which was time-consuming and inconsistent.

Solution: Built an AI voice agent that qualifies leads, handles cold calling, and books appointments across multiple outreach channels.

Result: Standardized outreach quality and freed up sales reps by automating lead qualification.

Problem: Creating lyric videos manually was slow and repetitive, requiring frame-by-frame timing work.

Solution: Built a pipeline that generates synced lyric videos using Python, OpenCV for rendering, and FFmpeg for output.

Result: Turned a hours-long manual editing task into an automated process with minimal input.

Problem: Publishing products with SEO-ready content and images to WooCommerce was slow and inconsistent.

Solution: Built an automated pipeline that generates SEO content and product images from Telegram input and publishes listings directly to the store.

Result: Cut product publishing time significantly while keeping listing quality and SEO consistent.

Problem: Agents spent excessive time manually sourcing leads, chatting with prospects, and scheduling follow-ups.

Solution: Built a system that scrapes leads, handles initial conversations with an AI chatbot, and schedules follow-ups via WhatsApp workflows.

Result: Gave agents a steady stream of pre-qualified leads without manual hours on outreach.

Problem: Manual ticket handling led to slow responses and missed customer requests.

Solution: Built an automated ticketing and response system connecting Telegram, n8n, and Google Sheets to log and route requests.

Result: Sped up response times and eliminated missed tickets by removing manual tracking.

Problem: Posting content across multiple social platforms manually was time-consuming and inconsistent.

Solution: Built an AI system with n8n that posts content to all major platforms from Google Sheets with no manual scheduling required.

Result: Fully hands-free content distribution across Instagram, TikTok, YouTube, Facebook, and more.

Problem: Freelancers lost billable hours because manual time tracking was easy to forget and inconsistent.

Solution: Built a Telegram bot that tracks billable hours using natural language via ChatGPT, Google Sheets, and n8n.

Result: Freelancers can log time with voice or text commands, eliminating lost billing hours.

Problem: Manually uploading email attachments to Monday.com was slow and prone to missed files.

Solution: Built a Zapier automation that monitors Outlook for emails with attachments, checks Monday.com, and uploads or creates items automatically.

Result: Eliminated manual file uploads and kept Monday.com records in sync with incoming emails.