I’ve been experimenting with a different direction for personal AI:
not cloud chatbots,
not another wrapper,
but a local-first cognitive operating system.
So I built EIDOLON OS.
An experimental AI system that combines memory, vision, semantic retrieval, CCTV intelligence, workflow replay, and local agent actions into one modular platform.
EIDOLON OS
A local-first AI cognitive operating system designed to transform raw desktop activity into structured, searchable memory.
Current Capabilities
- AI memory engine
- PDF intelligence
- Voice ingestion
- YOLO/OpenCV vision pipelines
- CCTV/video analysis
- Replayable activity timelines
- Agent workflows
- Semantic search
- Daily activity summaries
- Temporal memory graphs
Dashboard
[UPLOAD SCREENSHOT HERE]
Vision / CCTV Intelligence
EIDOLON can analyze uploaded videos and camera feeds using local computer vision pipelines.
Features include:
- motion detection
- object detection
- YOLO vision analysis
- event timelines
- temporal memory storage
[UPLOAD SCREENSHOT HERE]
Agent Workflows
The system also includes a local action/agent layer capable of:
- opening applications
- summarizing activity
- replaying sessions
- workflow intelligence
- contextual memory actions
[UPLOAD SCREENSHOT HERE]
Architecture
Built with:
- Next.js
- FastAPI
- TypeScript
- Python
- OpenCV
- YOLO
Everything runs locally.
No cloud dependency.
No telemetry.
No external memory APIs.
Why I Built This
Most AI systems today are stateless chat interfaces.
I wanted to explore something different:
an AI system that continuously remembers, observes, structures, and retrieves contextual information like a cognitive layer for the machine itself.
Still early.
But the foundation is becoming real.
