2.0 KiB
Architecture
Purpose
The Meeting Knowledge Assistant transforms recorded meetings into structured organizational knowledge through a modular processing pipeline.
Design Principles
- Architecture first
- Offline first where practical
- Immutable source data
- Replaceable AI components
- Small, focused modules
- Explicit interfaces
- Reproducible AI outputs
High-Level Pipeline
Recording ↓ Transcription ↓ Speaker Diarization ↓ Working Transcript ↓ LLM Analysis ↓ Knowledge Extraction ↓ Export
Domain Model
Meeting │ ├── Recording ├── Transcript │ ├── Canonical │ └── Working ├── Speakers ├── Participants ├── AI Artifacts ├── Knowledge Objects ├── Attachments └── Exports
Module Responsibilities
Recorder
Responsible only for capturing audio.
Input: None
Output: Recording
Transcription
Responsible only for speech-to-text conversion.
Input: Recording
Output: Canonical Transcript
Diarization
Responsible only for speaker identification.
Input: Recording + Canonical Transcript
Output: Working Transcript
LLM
Responsible for semantic analysis.
Input: Transcript
Output: AI Artifacts
Knowledge Extraction
Responsible for creating structured knowledge.
Input: AI Artifacts
Output: Knowledge Objects
Export
Responsible for creating user-facing documents.
Input: Knowledge Objects
Output: Markdown PDF DOCX
Artifact Lifecycle
Recording
↓
Canonical Transcript
↓
Working Transcript
↓
AI Artifacts
↓
Knowledge Objects
↓
Exports
Storage Strategy
The domain model is independent of the storage backend.
Possible implementations:
- File System
- SQLite
- PostgreSQL
- Cloud Storage
Future Extensions
- Live transcription
- Video processing
- OCR
- Semantic search
- Knowledge graph
- Company glossary
- Multi-language meetings
- Local LLM support