QuevaTech
QuevaTech: Architecture of the Future with Deep Tech, Advanced Engineering, and AI.
Roots deep. Branches forward.
A deep-tech venture born from academic research.
Developed Prototypes & Demos
Technical studies and prototypes developed in the laboratory environment
Security · Cryptography
Password API
High-entropy secure password and cryptographic key generation service derived from physical entropy sources.
Hardware · Entropy
TRNG Service
True random number generation based on quantum noise and thermal entropy. Cryptographic superiority over software methods.
Embedded System · FPGA
Enterprise TRNG Device
FPGA-based hardware random number generator for high-volume cryptographic operations. Secure boot and tamper-evident design.
Mobile · Flutter
Mobile Security Applications
iOS and Android applications built with Flutter. Local encryption, biometric authentication and zero-knowledge architecture.
AI · Entropy Analysis
AI-Hybrid Entropy Analyzer
Measurement and verification of entropy quality using deep learning models. 38% convergence improvement in Monte Carlo simulations.
Academic · Collaboration
Technical Consulting
Quantum-resistant cryptography integration, security architecture assessment and technical expertise sharing for academic collaboration.
Analysis · Simulation
Computational Analysis & Simulation
Analysis of large datasets using Monte Carlo methods, statistical modeling and numerical computation techniques.
Architecture · DevSecOps
Software Architecture & Infrastructure
Security-first software architecture design, DevSecOps pipeline setup and zero-trust infrastructure strategy.
Awareness · Human Factor
Social Engineering & Human Factor
Awareness research on the human dimension of cyber attacks. OSINT methodologies and behavioral security models.
Open Source Projects
Free software powering our research infrastructure
An open-source password manager and digital notebook where your data lives only on your device — no cloud required, no account needed. Military-grade security with AES-256-GCM encryption and Argon2id key derivation.
Zero Knowledge
Master password is never stored
Cross-Platform
One codebase, all platforms
Biometric Unlock
Face ID / fingerprint support
Security Architecture
Ana şifren Argon2id ile türetilir — brute-force saldırılarına karşı en güçlü standart
Oluşan anahtar yalnızca bellekte tutulur — diskte ya da sunucuda hiç saklanmaz
Her kayıt kendi benzersiz anahtarıyla şifrelenir — biri ele geçse diğerleri güvende
Comparison with Competitors
| Özellik | PassGuard | LastPass | 1Password | KeePass |
|---|---|---|---|---|
| Tam Çevrimdışı | ✅ | ❌ | ❌ | ✅ |
| Hesap Gerektirmez | ✅ | ❌ | ❌ | ✅ |
| AES-256-GCM | ✅ | ✅ | ✅ | ❌ CBC |
| Argon2id (varsayılan) | ✅ | ❌ | ❌ | ✅ |
| Native Mobil Uygulama | ✅ | ✅ | ✅ | ❌ |
| Güvenlik Olayı | Yok | Veri İhlali (2022) | Yok | CVE-2023-32784 |
QuevaTech in Numbers
Summary of our Academic R&D journey
Research Areas
Technical Documents
Prototype Demos
Lines of Code
Focus Research Areas
Our science-based technology development processes
Technical Infrastructure and Methodology
Data Analytics
We make it easy for you to make strategic decisions by transforming your large data sets into meaningful insights. Providing real-time processing and predictive insights with advanced analytics engine.
Machine Learning
We maximize your operational efficiency with predictive models and automation solutions. Enabling democratized AI development with AutoML capabilities.
Secure Infrastructure
Your data is safe in our cloud infrastructure protected by industry-standard security protocols. Ensuring comprehensive security with zero-trust architecture.
Revolutionary TRNG
True randomness generation with AI-Hybrid TRNG technology. Turn the unpredictability of the digital world to your advantage. Providing cryptographic-grade security with true randomness through physical entropy.
Our Infrastructure: Enterprise-Grade Architecture
Hybrid Cloud Deployment
Vendor lock-in elimination with multi-cloud strategy
Microservices Architecture
Scalable, maintainable service-oriented design
Kubernetes Orchestration
High availability with container-based deployment
Real-time Processing
Low-latency operations with stream processing capabilities
Secure by Design
Data protection at every layer with end-to-end encryption
Technologies We Integrate With
Core technologies used in our research and development processes
Python
TensorFlow
PyTorch
Kubernetes
Docker
C/C++
Rust
Linux
Git
GCP
Azure
PostgreSQL
MongoDB
Redis
Flutter
Platform Features
Unified Dashboard
Single pane of glass for all ML operations
Automated Pipelines
Code-free pipeline creation and management
Model Marketplace
Pre-trained models and components sharing
Collaboration Tools
Team coordination and knowledge sharing
Compliance Framework
Automated compliance with regulatory requirements
Integration & Compatibility
Data · Sources
Data Sources
SQL/NoSQL databases, data lakes, streaming platforms
Development
Development Tools
Python, Rust, C/C++, Flutter, VS Code, Jupyter
Deployment
Deployment Targets
Cloud, on-premise, edge and embedded system environments
Monitoring · Security
Monitoring Systems
Entropy quality monitoring, security audit logging, anomaly detection
Finance: Fast, Stable Convergence in Risk Modeling
In studies conducted within QuevaTech, the effects of the AI-Hybrid TRNG approach on Monte Carlo simulations are being investigated. Our research documents the potential of high-quality randomness to increase convergence speed and reduce the margin of error in risk analysis and portfolio optimization processes with technical metrics.
Analysis Accuracy and Convergence Improvement
Game Studios: Less Repetition, More Variety in Procedural Generation
The effects of hardware-based true random number generators (TRNG) on procedural content generation (PCG) are being tested in a laboratory environment. Our study demonstrates the success of improving seed quality in minimizing pattern repetitions and maximizing content diversity with scientific data.
Increase in Variation and Entropy Quality
Cybersecurity: Standards-Aligned Key and Session Randomness
Our research on the integration of physical entropy sources into cryptographic key generation processes aims for compliance with NIST SP 800-90A/B/C standards. The study technically analyzes the superiority of hardware-based solutions over software approaches in session confidentiality and key security.
Cryptographic Security and Standards Compliance
Open Source · Verifiable
Transparency and Trust
All our work is publicly available, independently auditable and documented.
Open Source Code
All projects are publicly available on GitHub. Review the code quality, architecture and security decisions yourself.
github.com/QuevaTechVirusTotal Scan
PassGuard binary files have been scanned by 70+ antivirus engines and came out clean.
0 / 70+ Tehdit TespitNIST Standard References
Our research is conducted with reference to NIST SP 800-90A/B/C standards. Our AI-Hybrid TRNG paper is published on arXiv.
SP 800-90A SP 800-90B SP 800-90C arXiv:2507.00145 ↗Deep Tech with Academic Roots
A deep-tech venture born from academic research, driven by scientific rigor. Based in Akyaka / Muğla, with a global vision.
Akademik Köken Ar-Ge Odaklı Akyaka · MuğlaAcademic Studies · R&D
Scientific Publications and R&D Blog
Latest notes from our academic studies and the technology ecosystem.
6G and Communication Architectures of the Future
Current research on 6G technologies investigates the effects of multimodal AI and edge computing integration on communication protocols. Our study addresses the role of next-generation models in human-machine collaboration from a technical perspective.
Post-Quantum Cryptography and Data Security
Cybersecurity architectures have entered a period of radical change with the rise of quantum computers. Zero-trust architecture and quantum-resistant encryption methods have become fundamental research topics for modern data governance.
MLOps Approaches in Hardware-Based Security
A technical review on the integration of production-grade machine learning pipelines (MLOps) into hardware-based security systems. The role of the Kubernetes and Kubeflow ecosystem in scalable infrastructure studies.
Physical Entropy and Randomness Analysis
The hybridization of physical entropy sources with artificial intelligence offers a new paradigm in true random number generation (TRNG) processes. QuevaTech's hybrid approach is analyzed for its effects on entropy quality and unpredictability.
YouTube · Duyurular · İçerik
QuevaTech YouTube Channel
Subscribe for research updates, technical analyses and academic content.
QuevaTech
@QuevaTech · youtube.com/@QuevaTech
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Research Updates
Technical content on TRNG, post-quantum cryptography and 6G
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Demo & Prototype Videos
Visual walkthroughs of PassGuard and FPGA prototype demos
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Announcements & New Projects
Open source releases and collaboration announcements
Latest uploads · QuevaTech
Founding Researcher
Hasan Yiğit
Founder of QuevaTech, conducting research in Deep Tech, AI, and true random number generation (TRNG). Working on physical-entropy-based TRNG technologies and 6G physical layer security.
QuevaTech is a deep-tech venture born from academic research, turning advanced engineering and AI architectures into real-world solutions. Our goal is to deliver technologies built with scientific rigor to the ecosystem as reliable, sustainable products.
Get In Touch
Fill out the form for academic collaboration or technical information requests.