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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
Product screenshot

Product Overview

Team Members

0
Not resourced

Cost Per Quarter

$9,765
Show breakdown

Usage

90,240minutes

Total duration of meeting processed

+46%
1,325

Number of meetings processed

+45%

Efficacy

112minutes

Average estimated time savings per minutes

0%
4.1/5

Quality of meeting minutes

+2%

Key Highlights

Q3-2024 Jul-Sep

  • Opened Noms for gated beta usage across multiple agencies.

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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