You will get a LangGraph Multi-Agent AI System for Complex Business Tasks
Project details
Some tasks are too complex for a single AI call. Research, then analyse, then write, then verify, then deliver — each step depends on the previous one, each requires different tools, and the whole sequence needs to run without human input. That is a multi-agent system.
I build LangGraph multi-agent pipelines where specialised agents collaborate on complex tasks. A research agent pulls data. An analysis agent processes it. A writing agent generates output. A quality agent reviews it. Each one is focused, each one is connected, and the whole system runs end to end autonomously.
LangGraph leads all agent frameworks in 2026 with 27,100 monthly searches — and I have built this in production. LeadForge is a live multi-agent B2B system where agents discover prospects, verify contacts, generate personalised emails, and fire drip sequences autonomously. Multi-agent is not a concept I read about. It is what I build. Substack
What you get:
LangGraph agent graph with clearly defined roles and handoffs
Tool integration — web search, database, API, or custom tools
Persistent state so the system remembers context between steps
FastAPI endpoint to trigger and monitor the pipeline
I build LangGraph multi-agent pipelines where specialised agents collaborate on complex tasks. A research agent pulls data. An analysis agent processes it. A writing agent generates output. A quality agent reviews it. Each one is focused, each one is connected, and the whole system runs end to end autonomously.
LangGraph leads all agent frameworks in 2026 with 27,100 monthly searches — and I have built this in production. LeadForge is a live multi-agent B2B system where agents discover prospects, verify contacts, generate personalised emails, and fire drip sequences autonomously. Multi-agent is not a concept I read about. It is what I build. Substack
What you get:
LangGraph agent graph with clearly defined roles and handoffs
Tool integration — web search, database, API, or custom tools
Persistent state so the system remembers context between steps
FastAPI endpoint to trigger and monitor the pipeline
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Gradio, Hugging Face, StreamlitAI Models
ChatGPT, GPT-4, LaMDA, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$75
|
Standard
$150
|
Advanced
$199
|
|---|---|---|---|
| Delivery Time | 4 days | 8 days | 12 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | |||
Model Documentation | |||
Model Monitoring | - | ||
Model Testing & Optimization | - | ||
Model Tuning | |||
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
Frequently asked questions
About Faizan
AI Automation Engineer | Claude, OpenClaw, LangGraph & n8n Developer
Saddiqabad, Pakistan - 11:02 am local time
✅ 1 live deployed multi-agent system (with a real URL — check it)
✅ 40% reduction in manual outreach effort for a real client
✅ Co-authored published research on multi-agent reinforcement learning (MAPPO/CTDE)
Most freelancers automate individual tasks. I build end-to-end agent systems that run your operations — including OpenClaw deployments, the open-source self-hosted AI agent framework that became the most starred project on GitHub in 2026.
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WHAT I BUILD
▶ Multi-Agent Pipelines (LangGraph · CrewAI · OpenClaw)
Stateful, production-grade agent systems with persistent memory, tool-calling, MCP integration, and human-in-the-loop controls. Not demos — systems that run in production across Telegram, WhatsApp, and Slack. Use cases: autonomous lead qualification, AI operations routing, research and reporting agents.
▶ AI Workflow Automation (n8n)
End-to-end n8n pipelines connecting your CRM, email, forms, Notion, Airtable, and APIs. Lead capture → AI scoring → CRM update → follow-up, running 24/7. Reduced manual operational overhead by 40% across live client deployments.
▶ Agentic RAG Systems
Knowledge systems built on your actual data — documents, website, internal wikis — using Qdrant, Pinecone, and LangGraph retrieval agents. Accurate, sourced answers 24/7. Not hallucinations. Your data, retrieved correctly.
▶ AI Lead Generation Engines
3 years of lead generation experience combined with production AI engineering. Systems that discover, verify, score, personalise, and outreach — automatically. LeadForge (live: leadforge-bice.vercel.app) is the proof.
▶ Full-Stack AI SaaS MVPs
FastAPI backend · Next.js frontend · vector DB · JWT auth · CI/CD. Production-ready AI products built to ship to users or show investors in weeks, not quarters.
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SYSTEMS SHIPPED
→ LeadForge — Autonomous Multi-Agent B2B Lead Engine
Llama 3 · Playwright · Hunterio · SMTP drip · LangGraph
Live at leadforge-bice.vercel.app — from lead discovery to Day-7 follow-up, zero manual input.
→ Agentic RAG Knowledge System
LangChain · FAISS · FastAPI · React · GitHub Actions CI/CD
Full-stack document Q&A deployed in under a week.
→ AI Career Mentor — SaaS MVP
FastAPI · PostgreSQL · Gemini API · Pydantic structured outputs · JWT auth
Resume analysis → personalised 12–24 week career roadmap. Structured AI outputs, not free-form hallucinations.
→ Lead Management Automation
n8n · Gemini AI · Docker
AI-driven lead scoring and follow-up. 40% less manual outreach for a real client.
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TECH STACK
AI Agents: LangGraph · CrewAI · LangChain · OpenClaw · OpenAI Agents SDK
LLMs: GPT-4o · Claude Opus/Sonnet 4.5 · Gemini 1.5 Pro · Groq · Llama 3
RAG: Qdrant · Pinecone · FAISS · Sentence Transformers · Agentic Retrieval
Automation: n8n · Python · Playwright · REST APIs · Webhooks · asyncio
Backend: FastAPI · PostgreSQL · Supabase · JWT Auth · Pydantic
Frontend: Next.js · React · TypeScript · Tailwind CSS
DevOps: Docker · GitHub Actions · CI/CD
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HOW I WORK
✔ Scope agreed with clear milestones before any code is written
✔ Clean, documented code — you own it completely
✔ Daily async updates on active projects
✔ No surprise scope creep
✔ Systems built for production, not demos that break under real load
If you have a manual bottleneck you want eliminated, message me and describe it in one sentence. I'll tell you directly whether I can automate it, how long it takes, and what it costs.
Steps for completing your project
After purchasing the project, send requirements so Faizan can start the project.
Delivery time starts when Faizan receives requirements from you.
Faizan works on your project following the steps below.
Revisions may occur after the delivery date.
Agent Architecture Design
I design the full agent graph — roles, tools, handoffs, and state schema — and share a diagram for your approval before writing any code.
Build, Test and Deploy
I build the full LangGraph system, test it end to end against real tasks, deploy the FastAPI endpoint, and deliver the GitHub repo with full documentation and Loom walkthrough.