Sentinel: Real-Time AI Fraud Detection

Enterprise-grade, event-driven anomaly detection pipeline with sub-millisecond ONNX inference.

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Sentinel is an enterprise-grade, real-time fraud detection system. It simulates high-throughput financial transactions via streaming (Redpanda/Kafka) and evaluates them in milliseconds using an optimized ONNX inference engine.

Quick Start

1. Clone the Repository

Clone the project to your local machine and navigate into the root directory:

    git clone https://github.com/enesgulerdev/sentinel.git
    cd sentinel

2. Configure Environment Variables

The data ingestion process requires a Google Drive File ID to fetch the raw dataset via gdown. Copy the example environment file to create your local configuration:

    cp .env.example .env

3. Install Dependencies

Install all required Python packages and set up the local development environment. This command utilizes uv to create a virtual environment and strictly syncs the dependencies locked in uv.lock.

    task env:install

4. Execute the ML Pipeline

Run the complete machine learning pipeline. This automated task will fetch the raw dataset using your provided .env variable, apply preprocessing transformations, and train the baseline model.

    task ml:pipeline

5. Launch and Manage Application

The Sentinel project utilizes a microservices architecture. Start the Docker containers to spin up the API gateway, and all other core services in detached mode:

    # Start all services
    task docker:on

    # Stop and remove containers, networks, and volumes
    task docker:off

Local Services & Ports

Once the Docker containers are up and running, you can access the core services via the following local addresses:

Service	Local URL
Dashboard:	http://localhost:8000/api/v1/dashboard
API Gateway	http://localhost:8000
Redpanda	http://localhost:8080

Troubleshooting

task: command not found

Sentinel leverages the Taskfile runner for all automation. If the command is not recognized, install it:

• macOS (Homebrew): brew install go-task
• Windows (Chocolatey/Scoop): choco install go-task or scoop install task
• Linux: sh -c "$(curl --location https://taskfile.dev/install.sh)" -- -d

Repository Structure & Deep Dives

Sentinel is built with a strictly modular architecture. While this guide covers local Docker deployment, you can explore the advanced components in their respective directories:

• Infrastructure & Kubernetes: Enterprise deployment manifests, service configurations, and orchestration details for scaling Sentinel in the cloud.
• Testing Suite: Comprehensive unit tests, integration tests, and mock fixtures ensuring system reliability.