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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
  • External recording and internal processing are separate responsibilities.
  • The processing pipeline must not depend on OBS-specific metadata or behavior.
  • Imported recordings must be treated like recordings from any other supported source.

High-Level Pipeline

External Recorder ↓ Audio Import ↓ Recording Validation ↓ Meeting Storage ↓ Transcription ↓ Speaker Diarization ↓ Working Transcript ↓ LLM Analysis ↓ Knowledge Extraction ↓ Export


Core Pipeline

External Recording

↓

Audio Import and Validation

↓

Transcription

↓

Speaker Diarization

↓

Working Transcript

↓

LLM Analysis

↓

Knowledge Extraction

↓

Storage and Export

Domain Model

Meeting │ ├── Recording ├── Transcript │ ├── Canonical │ └── Working ├── Speakers ├── Participants ├── AI Artifacts ├── Knowledge Objects ├── Attachments └── Exports


Module Responsibilities

Input and Ingest

Responsible for importing existing recordings into the application.

Initial reference source:

  • OBS Studio

Initial supported formats:

  • WAV

  • FLAC

Responsibilities:

  • validate the input file

  • collect technical metadata

  • calculate checksums

  • copy or move the recording into the meeting directory

  • create the initial Recording domain object

The ingest component must not perform transcription or modify the audio content.

Recorder

The recorder module is reserved for a future integrated recording implementation.

It is not required for the MVP.

The initial application workflow uses externally created recordings, with OBS Studio as the recommended reference recorder.


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

Imported Recording
    ↓
Validated Source Recording
    ↓
Canonical Transcript
    ↓
Working Transcript
    ↓
AI Artifacts
    ↓
Knowledge Objects
    ↓
Exports

---

## Initial Recording Strategy

The MVP does not implement platform-specific audio capture.

OBS Studio is the recommended reference recorder for online meetings.

The application initially processes existing WAV or FLAC recordings. Integrated

recording remains a future extension and must not be required by transcription,

diarization or analysis modules.

---

# 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