You will get a custom AI agent built with LangChain to automate your business workflows
Project details
You'll get a custom AI agent built with LangChain or LangGraph that actually does work for you — not just chats. The agent uses real tools (your APIs, databases, web search, email, Slack, Notion, CRMs), makes decisions, and completes multi-step tasks autonomously.
I'm a senior AI engineer who builds production agents, not demos. Whether you need a research agent that scours the web and writes reports, a support agent that handles tickets with your knowledge base, a sales agent that qualifies leads, or a complex multi-agent workflow with LangGraph — I'll design the right architecture and ship it.
Stack: LangChain, LangGraph, OpenAI / Anthropic / open-source LLMs, vector databases, FastAPI, Docker. Every agent ships with proper error handling, logging, retries, and a clean way for you to monitor what it's doing. Source code, deployment, and docs included.
I'm a senior AI engineer who builds production agents, not demos. Whether you need a research agent that scours the web and writes reports, a support agent that handles tickets with your knowledge base, a sales agent that qualifies leads, or a complex multi-agent workflow with LangGraph — I'll design the right architecture and ship it.
Stack: LangChain, LangGraph, OpenAI / Anthropic / open-source LLMs, vector databases, FastAPI, Docker. Every agent ships with proper error handling, logging, retries, and a clean way for you to monitor what it's doing. Source code, deployment, and docs included.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AIAI Development Language
PythonAI Tools
Hugging FaceAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$499
|
Standard
$1,299
|
Advanced
$2,999
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 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 Yaqov
Agentic AI Systems Architect | LLM Orchestration, Full-Stack & Busines
Shlomi, Israel - 7:44 am local time
With 20+ years of hands-on experience as a CTO and AI Systems Architect, I specialize in the most in-demand areas of 2026:
▸ AGENTIC AI & LLM ORCHESTRATION
Multi-agent systems, autonomous decision-making pipelines, RAG architectures for enterprise knowledge bases, and custom integrations with Claude, OpenAI, DeepSeek, Groq, and Ollama.
▸ BUSINESS PROCESS AUTOMATION
End-to-end workflow automation using n8n, Python, and custom AI agents. From lead management to customer service to data pipelines — I replace manual work with intelligent, scalable systems.
▸ FULL-STACK SAAS & API DEVELOPMENT
Production-ready platforms built with React, Next.js, FastAPI, Node.js, and PostgreSQL. Microservices architecture, real-time dashboards, and seamless API integrations.
▸ DATA ENGINEERING & AI ANALYTICS
Data pipelines, BI dashboards, predictive analytics, and NLP systems that turn raw data into business intelligence.
What sets me apart: I don't just write code — I own the entire lifecycle from strategy and architecture to deployment and scaling. Clients get a technical partner who understands both engineering and business outcomes.
If you need a specialist who can build, automate, and scale your AI-powered system end-to-end — let's create something exceptional together.
Steps for completing your project
After purchasing the project, send requirements so Yaqov can start the project.
Delivery time starts when Yaqov receives requirements from you.
Yaqov works on your project following the steps below.
Revisions may occur after the delivery date.
Define the agent's goal and tools
We map out the task, decisions, tools/APIs, and success criteria for the agent.
Build, integrate, and test
I build the agent in LangChain/LangGraph, wire up your tools and APIs, then test it on real cases.