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Production2025· Innomergence Solutions

AAR Generator

AI-assisted pipeline that converts meeting recordings and transcripts into structured After-Action Reports and DOCX documents.

PythonTranscription (AssemblyAI)RAG / vector retrievalOpenAIDOCX generationCloud storage

Interactive demo

aar-generator.local

Drop a meeting recording

MP3, WAV, or M4A · up to 2 hours

eoc-debrief-sample.mp3

18:24 · 26.1 MB

Ready

Portfolio simulation using local sample data

Select a meeting recording (sample).

Overview

An automated After-Action Report workflow. It takes meeting recordings and transcripts, applies speaker-aware processing and retrieval over reference material, and produces a structured summary exported as a Word document. Hours of note-writing become a reviewable draft.

Role: Full-Stack Developer

Approach & responsibilities

  • Built the transcription and speaker-labeling pipeline.
  • Implemented retrieval-augmented generation over reference material.
  • Designed structured summarization and automated DOCX output.
  • Handled the file-management workflow.

Key features

  • Audio transcription with speaker labels
  • Retrieval-augmented generation over reference docs
  • Structured, section-based summarization
  • Automated Word (DOCX) generation

Architecture

  1. Audio

  2. Transcription

  3. Speaker-labeled transcript

  4. Retrieval

  5. AI summary

  6. DOCX report

Challenges & decisions

  • Keeping generated reports faithful to the source transcript.
  • Producing consistent, well-formatted DOCX output.

Outcome

  • Turns raw meeting audio into a structured first-draft report automatically.

Privacy & demonstration note. The portfolio demonstration is local and non-functional: it visualizes the pipeline with an example transcript and report. No real recordings, transcripts, or model calls are used.