PersonalOS — Self-Hosted AI Agent Architecture
A personal R&D build: a self-hosted AI agent platform combining long-term memory, browser automation, voice processing, and proactive task management into a single system — built to stress-test agentic architecture patterns, not as client work.
The Challenge
What needed to be solved
Built independently to explore a hard architectural question: can a single agent maintain long-term context, take real actions (browser automation, scheduling), and run across a hybrid cloud/local inference setup without falling apart under everyday use.
What We Built
Developed a self-hosted AI agent powered by a dual-brain architecture that switches between cloud and local LLMs depending on task sensitivity and latency needs. Combines long-term memory via RAG, browser automation, voice transcription, and proactive scheduling, demonstrating patterns directly applicable to client-facing agentic systems.
Gallery
Project Screenshots
Stack Used
Technologies & Tools
Outcomes
Results & Impact
Automatically switches between cloud (Groq) and local (Ollama) inference.
Combines SQLite and ChromaDB for structured and semantic recall across sessions.
Patterns from this build inform agentic systems delivered to clients.
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