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Writing of meeting minutes, or Notes of Meetings (NOMs), within the government is a highly nuanced but tedious task. It can take anywhere from a few hours to a full civil servant’s work day. Pair Noms alleviates this effort by leveraging on advance LLM-based technologies to help transcribe, format and generate high-quality meeting minutes in under an hour.

SINCE 2024

Pilot
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Product Overview

Team Members

5

PM

1Engineer

Design

Ops

bryan-avatarhuiqing-avatarsheikh-avatarrachel-avatarjieyin-avatar

Cost Per Quarter

$222,126
Show breakdown

Usage

4,309minutes

Total duration of meeting processed

+155%
28

Number of agencies trialed

+211%
47

Number of meetings processed

+236%

Efficacy

125minutes

Average estimated time savings per minutes

0%
4.2/5

Quality of meeting minutes

+20%

Key Highlights

Q2-2024 Apr-Jun

  • Piloted Noms for various agencies across the government and collected insights for improvement of generation and interface.
  • Developed and refined heuristics of standards for meeting minutes in the government.
  • Built automated evaluation pipeline to assess generated minutes.
  • Moved past traditional LLM prompting and upgraded minutes generation pipeline to mimic secretariat workflow to improve meeting minutes quality.
  • Enhanced Noms editor interface to allow for faster referencing and editing.
  • Built auto scrubbing to corresponding point in the transcript with accompanying meeting audio playback.
  • Released in-built “Ask Pair” function to leverage on LLMs for faster edits.

Q1-2024 Jan-Mar

  • Built a feature to automate uploading of meeting material like audio recordings and slides.
  • Added audio compression to allow large files to be uploaded smoothly.
  • Built initial automated minutes generation pipeline for Pair Noms to turn raw transcripts into meeting minutes that capture the most salient points, are well structured, and worded in reported speech.
  • Prototyped minutes generation with DSPy framework to improve the quality of minutes generated.
  • Piloted minutes generation in meetings across 8 agencies, and collected feedback for further improvement.
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