You will get LangGraph AI Agents: Multi-Agent Systems & Workflow Automation
Project details
I build production AI agents for complex automation - not simple chatbots.
CAPABILITIES:
Multi-Agent Orchestration
• Complex workflows with parallel execution and state management
• Conditional routing, error handling, human-in-the-loop checkpoints
Tool Integration & Automation
• Any API: REST, GraphQL, databases, webhooks
• Data collection
• File processing: PDFs, spreadsheets, documents
Research-Grade Agents
• Multi-step information gathering and synthesis
• Autonomous decision-making with verification
REAL PRODUCTION EXPERIENCE:
• Travel booking agent with 4 API integrations serving live customers
• Document automation: 40h → 2h manual work
• Complex web data extraction
• Full-stack: LangGraph + FastAPI + deployment
WHAT MAKES THIS DIFFERENT:
I handle real business complexity: ambiguous inputs, edge cases, system failures. Not just linear workflows but intelligent systems that adapt. Production-ready code with error handling and monitoring.
Working systems that ship, not prototypes.
CAPABILITIES:
Multi-Agent Orchestration
• Complex workflows with parallel execution and state management
• Conditional routing, error handling, human-in-the-loop checkpoints
Tool Integration & Automation
• Any API: REST, GraphQL, databases, webhooks
• Data collection
• File processing: PDFs, spreadsheets, documents
Research-Grade Agents
• Multi-step information gathering and synthesis
• Autonomous decision-making with verification
REAL PRODUCTION EXPERIENCE:
• Travel booking agent with 4 API integrations serving live customers
• Document automation: 40h → 2h manual work
• Complex web data extraction
• Full-stack: LangGraph + FastAPI + deployment
WHAT MAKES THIS DIFFERENT:
I handle real business complexity: ambiguous inputs, edge cases, system failures. Not just linear workflows but intelligent systems that adapt. Production-ready code with error handling and monitoring.
Working systems that ship, not prototypes.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Google AutoML, MLflow, OpenCV, PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$200
|
Standard
$600
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | |||
Model Documentation | - | ||
Ontology | - | - | |
Source Code | - | - | |
Taxonomy | - | - |
Frequently asked questions
About Choi
AI Engineer: Vision, NLP, RL, Agent | SOTA Research meets Production
Seoul, South Korea - 11:23 pm local time
CORE CAPABILITIES:
AI Agent Systems (LangGraph/LangChain)
- Multi-agent architectures with state management and tool orchestration
- Human-in-the-loop workflows for complex decision-making
- API integration and async processing for production deployment
- Real deployment: Travel booking system with 4 API integrations serving live customers
Computer Vision
- Weakly-supervised semantic segmentation (56% mIoU COCO, beat SOTA)
- Object detection and tracking for real-time applications
- Medical imaging classification (94.5% ISIC benchmark)
- Self-training, multi-signal fusion (CLIP/DINO), custom architectures
NLP & Document Intelligence
- Large-scale document classification and routing systems
- Weak supervision frameworks with minimal labeled data
- Information extraction and semantic matching
- Production system: Automated 270+ file processing (40 hours → 2 hours)
Predictive Modeling & RL
- Ensemble methods: XGBoost, NGBoost, LightGBM, CatBoost
- Uncertainty quantification for high-stakes decisions
- Reinforcement learning for optimization problems
- Real impact: 3x improvement in bid success rate (₩7.7T market)
Production Engineering
- Web automation with anti-bot evasion (Playwright, Selenium)
- Async architectures for long-running AI tasks (FastAPI, Node.js)
- Database design, API development, frontend integration (React)
- Deployment: Docker, AWS, GCP, monitoring and error handling
WHAT MAKES MY WORK DIFFERENT:
I don't just train models - I build complete systems where AI components work together to automate complex workflows. Whether it's combining computer vision with NLP for document understanding, or integrating predictive models into multi-agent systems, I focus on end-to-end solutions that deliver measurable business value.
DELIVERABLES:
✓ Production-ready code with proper error handling and logging
✓ Clear documentation and architecture decisions
✓ Model training pipelines with evaluation metrics
✓ Deployment guides and monitoring setup
✓ Real results, not benchmarks
TECHNICAL STACK:
AI/ML: PyTorch, TensorFlow, Transformers, LangChain, LangGraph
Models: XGBoost, LightGBM, CatBoost, NGBoost, RL frameworks
Backend: Python, FastAPI, Node.js, async processing
Frontend: React, JavaScript
Automation: Playwright, Selenium, API integration
DevOps: Docker, AWS, GCP, monitoring tools
Based in Seoul (UTC+9), flexible for US/EU hours.
GitHub: github.com/HarimxChoi
Available for: AI agent development, computer vision systems, NLP applications, predictive modeling, end-to-end ML pipelines, production automation
Let's discuss how AI can solve your specific business problem.
Steps for completing your project
After purchasing the project, send requirements so Choi can start the project.
Delivery time starts when Choi receives requirements from you.
Choi works on your project following the steps below.
Revisions may occur after the delivery date.
Workflow Analysis & Architecture Design
Review your workflow, APIs, and business logic. Design agent architecture: tools needed, state management, decision flow. Create technical spec and confirm approach before coding.
Agent Development & Integration
Build LangGraph agent with tool integrations. Implement state machine, API connections, error handling, and retry logic. Set up async processing for long-running tasks.