You will get production-ready agentic AI system with LangGraph, memory, and custom tools
Project details
You will get a **production-ready Agentic AI system** using **LangGraph** for stateful orchestration, enabling structured reasoning, multi-step planning, and reliable task execution.
The system includes advanced **memory management**, combining short-term conversation memory with long-term semantic memory. It is also **context-positioning aware**, ensuring relevant context is prioritized and efficiently managed during long interactions.
I will integrate **MCP (Model Context Protocol) servers** to connect the agent with tools like Gmail, Calendar, Slack, databases, CRMs, and custom APIs. This enables the AI to take real actions, not just respond.
### Key capabilities:
• LangGraph-based stateful agent workflows
• Advanced short + long-term memory system
• Context-positioning aware reasoning
• MCP + custom API integrations
• Multi-step reasoning & autonomous execution
• Production-ready backend architecture
Built for real deployment with scalability, reliability, and clean architecture for automating business workflows and building intelligent AI agents.
The system includes advanced **memory management**, combining short-term conversation memory with long-term semantic memory. It is also **context-positioning aware**, ensuring relevant context is prioritized and efficiently managed during long interactions.
I will integrate **MCP (Model Context Protocol) servers** to connect the agent with tools like Gmail, Calendar, Slack, databases, CRMs, and custom APIs. This enables the AI to take real actions, not just respond.
### Key capabilities:
• LangGraph-based stateful agent workflows
• Advanced short + long-term memory system
• Context-positioning aware reasoning
• MCP + custom API integrations
• Multi-step reasoning & autonomous execution
• Production-ready backend architecture
Built for real deployment with scalability, reliability, and clean architecture for automating business workflows and building intelligent AI agents.
Programming Languages
PHP, JavaScript, PythonCoding Expertise
Cross Browser & Device Compatibility, Localization, DesignWhat's included
| Service Tiers |
Starter
$70
|
Standard
$200
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 4 |
Number of Pages | 1 | 2 | 5 |
Design Customization | - | ||
Content Upload | - | - | |
Responsive Design | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $100
Additional Revision
+$10
Content Upload
(+ 1 Day)
+$20
MCP Integration
(+ 1 Day)
+$40About Sajid
AI Systems Architect LangGraph Agentic AI RAG LLM Fine-Tuning
Lahore, Pakistan - 2:14 am local time
With 6 years of software engineering experience, I specialize in the full Agentic AI stack: from document ingestion and RAG pipelines to stateful multi-agent orchestration with LangGraph, MCP server integration, LLM fine-tuning, and private self-hosted deployments on GPU infrastructure.
━━ Agentic AI & LangGraph ━━
→ Stateful agent graphs with conditional edges and human-in-the-loop checkpoints
→ Multi-agent systems: supervisor, planner, and executor patterns
→ Deep Research agents with iterative reasoning loops
→ Chatbot memory: thread-level persistence, conversation summarization, semantic memory
→ ReAct, Plan-and-Execute, and reflection agent architectures
━━ RAG & Document Intelligence ━━
→ Document loaders: PDF, DOCX, HTML, Notion, S3, databases
→ Text splitters: recursive, semantic, and token-aware chunking strategies
→ Vector stores: Pinecone, PgVector, ChromaDB — with hybrid search and re-ranking
→ Multi-hop retrieval, query expansion, and contextual compression
━━ Tools & MCP Servers ━━
→ Custom tool design: web search, code execution, API calls, database queries
→ MCP server integration — connecting agents to Gmail, Calendar, Slack, and custom systems
→ Tool error handling, retries, fallback logic, and observability
━━ LLM Fine-Tuning ━━
→ Supervised Fine-Tuning (SFT) for domain adaptation
→ LoRA / QLoRA — efficient fine-tuning on GPU infrastructure
→ DPO — aligning model tone and behavior to business requirements
→ Dataset preparation: cleaning, formatting, augmentation (JSONL, ShareGPT format)
→ Models: Llama 3, Mistral, Qwen, Phi-3, DeepSeek
━━ Self-Hosted & Private AI ━━
→ Ollama deployment with open-source LLMs on your own server
→ GPU server setup on DigitalOcean / AWS (CUDA, Docker, NVIDIA drivers)
→ LangGraph + LangChain connected to self-hosted models — zero data leakage
→ Ideal for legal, healthcare, fintech, and GDPR-sensitive businesses
━━ Backend & Infrastructure ━━
→ Python (FastAPI, LangChain), Laravel, Vue.js
→ Async agent execution, streaming responses, WebSockets
→ Docker, Mysql, Redis for agent state persistence
→ Clean, documented, maintainable code — always
I don't just wrap an API and call it AI. I architect agents with proper memory, tool use, error handling, and production-grade infrastructure. Your system will be reliable, observable, and built to scale.
Available for hourly contracts and long-term engagements. I respond within a few hours — let's discuss your use case.
Steps for completing your project
After purchasing the project, send requirements so Sajid can start the project.
Delivery time starts when Sajid receives requirements from you.
Sajid works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement & System Design
Client shares requirements, workflows, and tool integrations. I define the agent architecture (LangGraph flow, memory design, and MCP/API connections) and finalize the system plan
Development & Integration
I build the agentic AI system with LangGraph orchestration, memory system, and MCP/custom tool integrations. Backend, APIs, and core logic are implemented and tested