# Roadmap

## Next Milestone: Meeting Assistant MVP GUI

Build the user-facing application over the validated Meeting Lab Python API.

- select an existing audio file
- reliably import WAV, FLAC and M4A through canonical FFmpeg preparation
- offer optional audio normalization, enabled by default
- create and edit Meeting Context through structured fields
- add and manage present and `mentioned_only` people
- optionally map `SPEAKER_XX` labels to participants with explicit confirmation
- configure and start `run_mvp_meeting(...)`
- display stage-based status and real progress when available
- handle completed and failed runs clearly
- display and edit the detailed generated protocol
- export the reviewed protocol

The milestone must keep diarization, GPU acceleration and fixed-duration audio
chunking optional. It must not launch the Meeting Lab CLI as a subprocess or
duplicate Meeting Lab processing logic.

Complete real-meeting validation of this vertical slice before expanding the
post-run workflow.

## Following Milestone: Distribution Protocol

- derive or generate a shorter participant-facing version
- allow review and editing before distribution
- export both detailed and short versions
- retain provenance linking each version to its transcript, configuration,
  prompt and model where practical

## Later Product Work

- speaker/name review with explicit human confirmation
- deterministic correction of suitable derived artifacts, beginning with a
  simple search-and-replace path
- protocol-only regeneration from existing transcription and diarization plus
  corrected mappings and Meeting Context
- transcript viewing and broader correction workflows
- recording and artifact lifecycle management
- search, tags, projects and meeting history
- richer Markdown, PDF and DOCX export
- optional SQLite indexing and full-text search
- integrated recording controls
- calendar and conferencing integrations
- semantic search and organizational knowledge features

## Research and Optional Extensions

- live transcription and real-time summaries
- company glossary and custom vocabulary
- voice identification with explicit consent and confirmation
- automatic name and speaker suggestions only as non-authoritative candidates
  for later human review
- audio cleanup
- OCR for shared screens
- RAG and knowledge-graph integration
- multi-language meetings and translation
- dual-model or evidence pipelines only if later validation demonstrates a
  material reliability benefit