[su-rì] • verb (Tagalog)
To analyze; examine.
The Enterprise-Grade, Local-First AI Attendance Platform.
Explore the Features »
Installation Guide
·
Report Bug
·
Request Feature
Suri is a desktop application for automated attendance tracking that respects privacy. The complete AI pipeline runs locally on the device.
Unlike cloud-dependent services, Suri executes all processing on local hardware. This eliminates network latency and keeps data under user control. The system can be used entirely offline, or with Secure Cloud Sync enabled to manage multiple devices.
| Local First | Privacy by Default | Hybrid Power |
|---|---|---|
| The AI runs 100% on the hardware (CPU/GPU). Face recognition takes mere milliseconds because it doesn't wait for a server. | Biometric data is encrypted on the device. It never leaves the machine unless Cloud Sync is explicitly enabled. | Optional "Split-Brain" Sync allows data backup and web reporting, without exposing raw face data to the cloud. |
Detailed technical documentation is organized into dedicated guides.
- Features & Capabilities - Details on Attendance Groups, Sessions, and Exports.
- Architecture & Stack - Understand the Electron + FastAPI + ONNX hybrid design.
- Installation & Setup - Step-by-step guide to get running in minutes.
- Troubleshooting - Diagnostic codes and environment flags.
- Privacy & Security - Management of biometric embeddings and data encryption.
Suri uses a modern, high-performance stack to deliver a native experience.
- Core AI: Local Face Recognition & Liveness Detection.
- Data Management: CSV Import/Export & Group Management.
- Multi-Camera: Support for parallel RTSP streams.
- Remote Dashboard: Optional web-based admin panel.
- Mobile Companion: Check-in app for attendees.
Visit the issues page to submit feature requests.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the AGPL-3.0 License. See LICENSE for more information.
This project relies on open source software. See Third Party Licenses for details.