Cognitive AI Researcher | Local-First Intelligence Architect | Swift & Python Developer
Building controllable, personal AI systems that operate at the speed of connection
I'm building Mavaia — a Cognitive-Local Language Model (C-LLM) that structures intelligence through adaptive cognitive architectures operating independently of model inference. This represents a new category of AI systems that prioritize local-first deployment, persistent memory, and emotional continuity.
Key Research Areas:
- 🧠 Adaptive Cognitive Layers — Multi-component pipelines for cognitive processing
- 💾 Persistent Memory Systems — Cross-conversation continuity and semantic clustering
- 🛡️ Safety Protocols — Multi-layer intervention frameworks for mental health and safety
- 🔧 Tool Calling Architecture — Multi-turn agent frameworks for dynamic capability integration
- 🎯 Local-First Intelligence — On-device cognitive processing with privacy preservation
A production C-LLM system with adaptive cognitive architecture
- ✅ Ten-component Adaptive Cognitive Layer (ACL) pipeline
- ✅ Persistent memory with cross-conversation continuity
- ✅ Multi-layer safety protocols for mental health and safety
- ✅ Tool calling architecture with 18+ tools across 8 categories
- ✅ Local-first deployment with privacy preservation
Technical reports and research documentation
- 📄 15+ comprehensive technical reports
- 🔬 Cognitive architecture research
- 📊 Evaluation frameworks and benchmarks
- 📖 Academic publications
- TR-2025-60: Thynaptic Intelligence Ecosystem Framework
- TR-2025-59: Mavaia System Status and Progress
- TR-2025-58: Tool Calling Architecture
- TR-2025-57: Memory Systems Architecture
- TR-2025-56: Architectural Safety Protocols
- 🔬 Research: Advancing C-LLM architecture and evaluation frameworks
- 🛠️ Development: Enhancing Mavaia's cognitive capabilities and tool integration
- 📊 Evaluation: Expanding benchmark coverage and performance metrics
- 📖 Documentation: Publishing technical reports and architectural documentation
- Advanced cognitive architecture patterns
- Multi-agent orchestration systems
- On-device machine learning optimization
- Safety and alignment research
I'm always interested in:
- Collaborating on cognitive AI research
- Discussing local-first intelligence architectures
- Exploring safety and alignment in AI systems
- Sharing knowledge about Swift, Python, and AI development
Feel free to reach out!
"Thinking systems at the speed of connection."
Building the future of controllable, personal AI