You will get a LangGraph AI Support Agent with SQL Database Tools
Project details
You will get a production-ready AI Support Agent built with LangGraph that answers questions by safely querying your database using tool calling. Unlike basic chatbots, this agent follows a controlled workflow (supervisor + approved tools), validates inputs, and returns structured answers for records such as customers, orders, invoices, or tickets. Delivered as a Streamlit demo with clean setup (requirements + .env.example) and clear handover documentation. Default mode is read-only for safety, with optional upgrades for role-based access, logging, and cloud deployment.
AI Algorithms
Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Tools
GitHub Copilot, Hugging Face, PyTorch, Streamlit, Word2vecAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$299
|
Standard
$599
|
Advanced
$999
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 8 days |
Number of Revisions | 2 | 3 | 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 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$120 - $200
Additional Revision
+$75
Database Setup (SQLite/Postgres)
(+ 2 Days)
+$250
Role-Based Access Rules
(+ 2 Days)
+$200
Cloud Deployment
(+ 2 Days)
+$200Frequently asked questions
About Ahmed
Generative AI Engineer | RAG Chatbots | LangGraph Agents | Vector DB
Bani Suwayf, Egypt - 5:39 am local time
What I deliver
Document Chatbots (RAG): Upload PDFs/Docs → chat with your knowledge base (with sources/citations)
Database-Connected Support Agents: AI that can safely query invoices/orders/customers (SQL tools)
LangGraph multi-agent workflows: supervisor + specialized agents + tool calling + memory
Streamlit demos + deploy-ready code: reproducible setup, documentation, and handover
Tech stack
Python, LangGraph, LangChain, Gemini (Google), Chroma/Vector DB, SQL/SQLite, Streamlit
How I work
Understand your data source (docs/DB/website) and top questions
Build a working demo fast (so you can test it early)
Deliver clean, documented code + deployment instructions
If you share your documents or database schema and the top questions the assistant must answer, I’ll propose the simplest architecture and start immediately.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Scope confirmation
Review your database type, schema, sample questions, and access rules (read-only vs write). Confirm what data the agent is allowed to access.
Tool design & safe queries
Create approved database tools (functions) and implement safe query patterns (validation + parameterized queries) to prevent unsafe or out-of-scope access.