AI Agent Development Projects in Pakistan
AI Agent Development Projects in Pakistan
Sign Up
Post a job
Sign Up
Log In
Filters
2
Projects
People
3
Toolshed (Data, Automation, AI Agents, Framer, Retool)
max
Development of Financial Management Platform for Vergo
3
200
3
Muhammad Haseeb
pro
Built an autonomous AI agent that scrapes and updates 500K+ awards from across the web. The system intelligently finds new awards and refreshes existing data, reducing manual work by 80% and slashing update cycles from 6 months to just 3-4 weeks. Runs independently with minimal supervision.
2
3
88
1
syed zain hasan
StonAI
1
6
0
Muhammad Hassan
News Mind AI – Multi Agent AI News Engine
0
14
0
Muhammad Sohaib Amin
AI-Powered Email Classification & Auto-Responder Workflow
0
7
0
Rahees Ahmed
Browser Agent AI-powered browser automation with Vision and LangGraph. An intelligent agent that can see, understand, and interact with web pages like a human. Built on LangGraph for robust state management and Ollama for flexible local or cloud-based vision models.
0
4
1
Taimoor Khan
My AI agent was working… but I had no idea why it worked sometimes and completely fell apart other times. That’s when I plugged in LangSmith , and realized I’d been flying blind. Suddenly, my “agentic AI” wasn’t a black box anymore, I could see everything: Every tool call, LLM invocation and retry the agent made, also token burned & cached, state transition across agent steps What surprised me most wasn’t the bugs , it was the waste. One trace showed my system prompt alone was 6.5k tokens. Not because it needed to be… but because I never saw it before. So I fixed it. Refactored prompts -> 1.5k tokens, same output quality Switched to dynamic system prompts, injected only when complexity demanded it Lesson learned: If you’re building agentic systems without observability
1
54
0
Keshave Malhi
Automated Refund Request Workflow
0
3
2
Devloom ai
Voice-Activated AI Assistant with Memory using n8n
2
11
0
Qadeer Ahmed
AI-Powered Voice Assistant with RAG Workflow
0
0
2
ADEEL AHMED
SecOps
2
1
0
Waqas Shah
pro
Automating Session Tracking with n8n for a Coaching Business Just wrapped up this n8n workflow for one of my clients, a coaching business that manages dozens of client sessions every week. I built this automated workflow 👇 🧠 How it works: 1️⃣ Triggers when a Google Calendar session ends. 2️⃣ Extracts the client’s name from the event title. 3️⃣ Fetches client info from Google Sheets. 4️⃣ Subtracts one from the remaining sessions count. 5️⃣ Updates the sheet automatically, no manual input needed. 6️⃣ Finds the next scheduled session from the calendar. 7️⃣ Sends an automated message via Bird API (WhatsApp) to the client confirming their next session. 💼 Impact for the client: Saved 2+ hours daily on manual admin work. Reduced scheduling mistakes by 100%. They now get automatic session reminders and updates.
0
163
2
Zaviyaar Bin Irfan
I created a marketing n8n workflow integrated with DataForSEO, LinkedIn, GCP, PiAPI and Slack. Given a topic on Slack, it will use DataForSEO to get top trending and relevant keywords against which it will generate blog headings. Once the user chooses one on slack, it will perform a web search to write a blog with proper guidelines and hashtags. PiAPI is used to generate an image using FLUX model and then run a custom HTTP request to upload to LinkedIn and Wordpress.
2
121
2
Muhammad Haseeb
pro
Built the complete AI backend for a B2B SaaS serving 10K+ users, processing 100K+ invoices monthly. Developed custom AI models with LLM-powered multi-agent orchestration using Python and FastAPI. The system automates invoice extraction and validation, handling complex workflows at scale.
2
2
151
1
Muhammad Talha
MediBot - Medicine Suggestion AI Bot
1
2
0
Syed Ali
Built an MVP for a Metrominal Service AI Chatbot I recently developed an MVP for an AI-powered service chatbot designed for Metrominal. This generative chatbot helps users resolve issues instantly by understanding their queries, guiding them through solutions, and providing accurate responses in real time. The system is powered by a RAG (Retrieval-Augmented Generation) pipeline, enabling the chatbot to communicate directly with company data. It retrieves relevant documents, processes information, and generates context-aware answers, ensuring reliability and up-to-date results. The MVP demonstrates how AI can streamline customer support, reduce response times, and make organizational data easily accessible to end users through a natural, conversational interface.
0
82
Explore projects