You will get a custom AI agent built with LangChain or LangGraph
Rising Talent
Rising Talent
Project details
Most AI integrations stop at "send a message, get a reply." I build agents that actually do things: search your documents, query your database, classify and route requests, call external APIs, and hand off to a human when the situation calls for it.
I've shipped a multi-agent LangGraph pipeline that autonomously triages and resolves support tickets with full reasoning traces, an NL2SQL agent that lets non-technical teams query a live database in plain English, and a RAG system that answers questions from legal contracts with exact citations and page numbers. The common thread across all of them: the agent has to work reliably in production, not just look good in a demo.
Clients come to me when they need a document Q&A system their team can actually trust, an agent that automates a multi-step workflow end to end, an AI feature added cleanly to an existing product, or an MVP built from scratch.
Have something specific in mind? Message me before ordering and we'll figure out the right approach.
I've shipped a multi-agent LangGraph pipeline that autonomously triages and resolves support tickets with full reasoning traces, an NL2SQL agent that lets non-technical teams query a live database in plain English, and a RAG system that answers questions from legal contracts with exact citations and page numbers. The common thread across all of them: the agent has to work reliably in production, not just look good in a demo.
Clients come to me when they need a document Q&A system their team can actually trust, an agent that automates a multi-step workflow end to end, an AI feature added cleanly to an existing product, or an MVP built from scratch.
Have something specific in mind? Message me before ordering and we'll figure out the right approach.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Keras, MLflow, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$70
|
Standard
$100
|
Advanced
$130
|
|---|---|---|---|
| Delivery Time | 3 days | 4 days | 5 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Frequently asked questions
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NW
Nifra W.
Jul 29, 2026
LangGraph Engineer for Multi Agent Orchestration and State Machine Architecture
Abdullah did a fantastic job building out our multi-agent architecture! He set up the pipeline smoothly and handled all the routing and error handling cleanly. Super easy to communicate with and reliable from start to finish. Highly recommend!
DK
Djjik K.
Nov 3, 2024
Fix errors
Abdullah was fantastic to work with! He showed great expertise, delivered quality work on time, and communicated effectively throughout the project. I would highly recommend him and would gladly work together again!
About Muhammad Abdullah
Full Stack AI Developer | AI Agents, Voice AI Automation, Python, n8n
100%
Job Success
Bahawalpur, Pakistan - 3:06 am local time
I build production-ready AI solutions that automate complex workflows, streamline business operations, and integrate with your existing backend architecture.
From 𝐀𝐈 𝐂𝐡𝐚𝐭𝐛𝐨𝐭𝐬 and 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 to custom APIs and custom workflow orchestrations, every solution is engineered to deliver measurable business outcomes.
I help businesses build custom AI applications from the ground up. Engineering autonomous 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬, integrating OpenAI and Anthropic LLMs into existing products, developing RAG-powered knowledge systems, and delivering ultra-low-latency 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧.
By leveraging custom Python code and n8n (self-hosted or cloud), I craft enterprise-grade automations and backend systems designed to perform reliably under high load.
➤ 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
AI Development & Agents:
AI Agents, Voice AI Automation, LangChain, LangGraph, RAG Pipelines, Prompt Engineering, Model Integration Workflows, OpenAI, Claude, LLM Integration
Intelligent Orchestration & Automation:
n8n (Self-Hosted & Cloud), Custom AI Workflow Automation, Webhooks, API Integration
Backend Development:
Python, FastAPI, Django, REST API Architecture, Async Python
Databases & Vector Storage:
PostgreSQL, MySQL, MongoDB, Pinecone, Qdrant, ChromaDB, Vector Databases
➤ 𝐑𝐞𝐜𝐞𝐧𝐭 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
✅ 𝐆𝐦𝐚𝐢𝐥 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 | 𝐄𝐦𝐚𝐢𝐥 𝐓𝐫𝐢𝐚𝐠𝐞 & 𝐑𝐀𝐆 𝐑𝐞𝐩𝐥𝐲 𝐃𝐫𝐚𝐟𝐭𝐢𝐧𝐠 𝐢𝐧 𝐧𝟖𝐧
An inbox receiving 100+ emails a day consumes hours of manual sorting. I built an end-to-end self-hosted system that reads incoming mail, categorizes it by urgency, and writes a draft reply grounded in the client's internal policy documents. Drafts are left directly in the thread for human approval. Newsletters and automated notifications are filtered and skipped. The solution operates across 4 workflows with 24 nodes at ~3s per email, ensuring zero sensitive policy data leaves the client's infrastructure.
𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤:
• n8n (Self-Hosted)
• Python & REST APIs
• Retrieval-Augmented Generation (RAG)
• AI Agent Development
𝐏𝐫𝐨𝐛𝐥𝐞𝐦: Teams receiving 100+ emails/day spend hours sorting messages before drafting responses, while third-party SaaS "AI tools" pose data security risks and lack human control.
𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Engineered a self-hosted n8n workflow that classifies incoming email, drafts RAG-backed replies using internal company policies, and presents the draft inside Gmail for single-click human approval.
𝐑𝐞𝐬𝐮𝐥𝐭: Converted hours of manual triage into instant human approvals, ensuring accurate, policy-grounded replies with full data privacy.
✅ 𝐀𝐈 𝐕𝐨𝐢𝐜𝐞 𝐀𝐠𝐞𝐧𝐭 | 𝐀𝐟𝐭𝐞𝐫-𝐇𝐨𝐮𝐫𝐬 𝐅𝐫𝐨𝐧𝐭 𝐃𝐞𝐬𝐤 (𝐁𝐫𝐢𝐠𝐡𝐭𝐥𝐢𝐧𝐞 𝐃𝐞𝐧𝐭𝐚𝐥)
Replaced a dental practice's after-hours voicemail with a real-time conversational AI voice agent. The agent handles incoming calls, determines user intent, queries live calendar availability, books appointment slots, and sends instant SMS confirmations during the call. Emergency situations are immediately routed to on-call staff, while complex pricing/insurance questions are flagged and logged to a central dashboard with full call recordings and transcripts.
𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤:
• Voice AI (Vapi / Twilio)
• Python Backend APIs
• Conversational AI & Prompt Engineering
• Custom Webhooks & Calendar Integration
𝐏𝐫𝐨𝐛𝐥𝐞𝐦: Dental practices lose high-value leads and fail to escalate urgent after-hours emergencies due to static voicemail systems.
𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Built a custom voice agent operating at ~0.2s latency featuring real-time calendar booking, automated SMS follow-ups, and a two-layer emergency classifier.
𝐑𝐞𝐬𝐮𝐥𝐭: 100% of after-hours calls are now instantly booked, triaged, or escalated, eliminating missed leads and improving patient care.
Let's chat if you're looking for a Full Stack AI Developer to build AI Agents, Voice AI Automation, custom RAG pipelines, or complex Python/n8n backend workflows.
Whether you need custom Python services or scalable n8n orchestrations integrating OpenAI, Claude, or open-source LLMs, I'm just a message away! 📩
Steps for completing your project
After purchasing the project, send requirements so Muhammad Abdullah can start the project.
Delivery time starts when Muhammad Abdullah receives requirements from you.
Muhammad Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Scope and architecture
Review your requirements, confirm what the agent needs to do, what data it works with, and what tools it connects to. Agree on the approach before writing any code.
Prompt engineering and agent design
Design the agent's reasoning flow, tool definitions, memory strategy, and guardrails. For RAG systems, design the chunking, embedding, and retrieval pipeline.