AI Deploy Network / Builder
AI Engineer building autonomous agents and practical AI automation. Open to open-source collaboration. Sharing projects, experiments, and lessons.
Published evidence
1 AI Deployment
1 publicly identified
01
I’m an AI agent developer from Gujranwala, Pakistan.
My main live deployment right now is a transaction verification agent for a US client. It monitors 50+ WhatsApp groups, pulls payment screenshots, runs them through an OCR and Gemini Vision pipeline, and cross-references results against Stripe before flagging anything as fake or duplicate. I built the WhatsApp integration, the FastAPI OCR service, and the n8n orchestration layer. It runs on DigitalOcean 24/7.
Outside that: an n8n lead generation pipeline that goes from form submission to personalized outreach in one automated chain, a WhatsApp restaurant chatbot with sub-3-second response time, and CodeScope, an MCP server I built for AI coding agents.
I work at the orchestration layer. LLMs connected to real external tools, deployed on real infrastructure, not mocked APIs.
02
Implementation records and publicly available work, where published.
1 AI Deployment delivered, including 1 publicly identified implementation available to inspect.
period not specified
Automated 12 hours (period not specified)
period not specified
Reduced operating costs by USD 10,000 (period not specified)
period not specified
Generated USD 50,000 additional revenue (period not specified)
Builder-reported outcomes, recorded on deployment and case study records that AI Deploy Network reviewed before publication. AI Deploy Network does not currently capture a measurement basis or calculation methodology for reported outcomes, so none is shown.
03
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
AI Agents
Autonomous Agents
Computer Vision
Multi-Agent Systems
RAG & Knowledge Retrieval
04
Real AI implementations demonstrated through evidence.
Autonomous agent monitoring 50+ WhatsApp groups for payment screenshots, classifying each transaction as Valid, Fake, or Duplicate in real time using OCR, Gemini Vision, and Stripe verification.
12 hours automated / per day · USD 10K cost savings / per month · USD 50K reported revenue impact / per month
Credit Unions · AI Agent · Workflow Automation
View Deployment05
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
06
Technologies listed by the Builder, distinguished by published evidence.
No published evidence linked yet.
07
Published Deployments support the listed counts. Other industries are Builder declared.
1 published Deployment
Builder declared
Builder declared
Builder declared
08
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
The platform does not independently audit client systems or financial records. How this is verified
DIGITAL AQ LLC
automation Bot • FinTech
Client: AQ Digital LLC (US-based) Status: Live in production The problem: The client operated payment workflows across 50+ WhatsApp groups. Manually verifying whether payment screenshots were real, fake, or already submitted was slow, error-prone, and not scaling. What I built: An autonomous transaction verification agent that monitors those groups in real-time. When a payment screenshot arrives, the system extracts transaction details through an OCR pipeline (Tesseract primary, Gemini Vision fallback), cross-references the result against Stripe, and classifies it as Valid, Fake, or Duplicat
MDA Restaurant
Automation • Restaurants & Food Service
Client: MDA Restaurant Status: Built and deployed The problem: The restaurant was handling customer queries, orders, and stock questions manually over WhatsApp. Every FAQ reply, order confirmation, and inventory check required staff time, and response consistency was unreliable. What I built: An AI-powered WhatsApp chatbot that handles the full customer interaction loop autonomously. A customer sends a message, the Gemini AI agent reads it, resolves the intent, and responds. Orders get appended to a Google Sheet. FAQs are answered from a live reference sheet. Stock queries pull from the inve
SoftShack Company
Automation • Marketing & Advertising
Status: Built and deployed The problem: Manual lead generation is slow at every step finding businesses, filtering duplicates, researching contact details, and writing outreach emails all require separate effort. Most teams either skip enrichment or send generic emails. Both hurt conversion. What I built: An end-to-end AI lead generation pipeline that takes a form submission and outputs a personalized outreach email with no manual steps in between. The agent scrapes Google Maps for businesses matching the target criteria, filters duplicates before going further, scores and classifies each
Claude Code in Action
Anthropic
Issued Sep 2026
Credential ID: dfdqykuqsfq9
Start Writing Prompts like a Pro
Courera
Issued Jun 2026
Credential ID: M6CC2EAXTATR
Certificate of completion: Claude 101
Anthropic
Issued Mar 2026
Credential ID: vem59s7ghqed
Certificate of Completion: Al Fluency Framework & Foundations
Anthropic
Issued Mar 2026
Credential ID: 9mzurkrs8b2r
Tell Ibadat Ali what you are trying to automate and the outcome you need. Your message goes directly to the builder, with a copy kept in your Organisation Workspace.
