Datasaur AI

AI-powered ticket processing and intelligent request routing system using FastAPI, PostgreSQL and LLM-based classification.

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Overview

Datasaur AI is an experimental AI-driven support ticket processing platform designed to automate ticket analysis, classification, routing, prioritization, and intelligent request handling.

The platform combines:

• FastAPI backend architecture,
• AI-powered text analysis,
• structured ticket processing,
• automated request routing,
• CSV data pipelines,
• and intelligent support workflow optimization.

The project was developed as part of the F.I.R.E Challenge and explores the integration of AI systems into enterprise support environments.

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Features

• AI-powered ticket classification
• Intelligent request routing
• Ticket prioritization
• Language detection
• Sentiment analysis
• Automated category assignment
• Manager assignment logic
• SLA-aware processing
• CSV-based data pipelines
• FastAPI backend API
• PostgreSQL integration
• Structured ticket analytics

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AI Integration

The system integrates Large Language Models for:

• ticket classification,
• sentiment analysis,
• language detection,
• automated summaries,
• and intelligent routing decisions.

AI components enable:

• faster request handling,
• reduced manual workload,
• and improved operational efficiency.

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System Architecture

Incoming Tickets
        ↓
CSV/Data Processing Pipeline
        ↓
AI Classification Engine
        ↓
Language & Sentiment Analysis
        ↓
Priority Assignment
        ↓
Manager Routing Logic
        ↓
FastAPI Backend
        ↓
PostgreSQL Database
Tech Stack
Backend
Python
FastAPI
SQLAlchemy
Pydantic
Database
PostgreSQL
AI
OpenAI API
NLP processing
Text classification
Infrastructure
REST API architecture
CSV processing pipelines
Project Structure
Datasaur/
│
├── app/
├── templates/
├── DataSaur/
│
├── main.py
├── requirements.txt
├── tickets.csv
├── managers.csv
├── business_units.csv
└── README.md
Core Components
Ticket Processing Engine

The system processes support tickets and automatically extracts:

ticket category,
business unit,
customer sentiment,
request language,
urgency level,
and routing metadata.
AI Classification

AI models are used for:

intelligent ticket categorization,
automated summaries,
priority estimation,
and workflow optimization.
Routing System

The routing engine distributes tickets based on:

business unit,
manager skills,
workload,
language,
and SLA requirements.
API Usage

Run the FastAPI server:

uvicorn main:app --reload

Default local server:

http://127.0.0.1:8000

Swagger API documentation:

http://127.0.0.1:8000/docs
Installation

Clone repository:

git clone https://github.com/A984j983/Datasaur.git

Move into project folder:

cd Datasaur

Install dependencies:

pip install -r requirements.txt

Run application:

uvicorn main:app --reload
Future Improvements

Planned future features:

real-time dashboard,
advanced analytics,
multi-agent routing systems,
vector search,
RAG integration,
memory-based support agents,
and autonomous workflow optimization.
Research Focus

This project explores:

AI-driven workflow automation,
intelligent support systems,
ticket routing optimization,
NLP classification,
and enterprise AI integration.
Author
Ardak Bolat

Astana IT University
Bachelor Degree in Information Security

GitHub:
https://github.com/A984j983

LinkedIn:
https://linkedin.com/in/ardak-bolat-2601b22ab