Less manual note taking and review effort
Automated transcription and summarisation reduce repeated manual note preparation.
AI product case study
MeetSage
AI powered meeting capture, transcription, analysis, reports and conversational follow up.
MeetSage is an AI powered meeting intelligence platform built to help professionals, teams, consultants, agencies, and business leaders convert meetings into structured knowledge. The platform combines a web app, MeetSage browser extension, Google Drive integration, AI transcription, AI analysis, PDF reports, and contextual meeting chat.
Project classification: This project showcases a meeting intelligence product for professionals and teams.
Clearer action items and decisions
Structured summaries make decisions, action items and follow up responsibilities easier to review.
Searchable meeting context
Conversational search gives users a way to retrieve context from previous meetings.
01 / Business context
Who needed the solution
MeetSage is an AI powered meeting intelligence platform built to help professionals, teams, consultants, agencies, and business leaders convert meetings into structured knowledge. The platform combines a web app, MeetSage browser extension, Google Drive integration, AI transcription, AI analysis, PDF reports, and contextual meeting chat. The goal is simple: help users stop losing important meeting insights inside long recordings and scattered notes without paying anything. MeetSage does not just store meetings.
02 / Challenge
What needed to change
Most teams record meetings, but the value inside those meetings is hard to reuse. Common challenges include: • Long recordings are difficult to review • Action items are often missed • Decisions are not documented clearly • Follow ups take manual effort • Meeting notes are scattered across tools • Teams cannot easily search past discussions • Shared access is difficult to manage • Recordings are stored, but not converted into business intelligence The real problem is not recording meetings.
Long meeting recordings were difficult to reviewThis created avoidable manual review, inconsistency or operational risk in the existing workflow.
Action items and decisions were frequently missedAction items are often missed.
Follow up required manual note preparationFollow ups take manual effort.
Meeting context was scattered across toolsMeeting notes are scattered across tools.
Teams could not easily query previous discussionsTeams cannot easily search past discussions.
03 / Workflow transformation
Before and after
Previous workflow
- Long meeting recordings were difficult to review
- Action items and decisions were frequently missed
- Follow up required manual note preparation
- Meeting context was scattered across tools
- Teams could not easily query previous discussions
Structured workflow
- Capture or upload meetings
- Transcribe conversations
- Structure summaries and actions
- Query meeting context
- Review structured outputs
04 / Solution
How we approached it
MeetSage uses AI to turn meeting recordings into structured, useful outputs. The platform supports: • AI transcription of meeting recordings • Structured meeting summaries • Action items and decisions • Risks, blockers, and next steps • AI generated follow up email drafts • PDF meeting reports • Chat with meeting transcript • Shared meeting access by email Users can ask questions like: • What were the final action items? • What did the client say about pricing? • Write a follow up message from this meeting. • Summarize only the product discussion.
Capture or upload meetings
Accept meeting recordings through the product and supporting extension workflow.
Transcribe conversations
Convert audio into time aligned meeting text.
Structure summaries and actions
Extract summaries, decisions, owners and follow up tasks.
Query meeting context
Allow users to ask grounded questions across the captured meeting.
05 / Example workflow
From input to reviewable output
1Capture or upload meetings
2Transcribe conversations
3Structure summaries and actions
4Query meeting context
5Review transcript and summary
6Approve actions and follow up
06 / Delivery scope
What the delivery covered
Business and product workflow
- MeetSage Extension
- Ai Transcription Of Meeting Recordings
- Structured Meeting Summaries
AI, data and automation
- Structured AI workflow
- Data processing and validation
Application and cloud engineering
- Angular
- FastAPI
- MongoDB
- Docker
Scope boundary
The case study covers meeting capture, transcription, summarisation, reports and chat. Production deployments must separately define consent, supported languages and data retention.
07 / Architecture and controls
How the system is organised
Angular
FastAPI
MongoDB
Docker
JWT
Authenticated access
Meeting records and reports are accessed through authenticated application workflows.
Reviewable summaries
Users can review transcripts, summaries and action items before using them downstream.
Consent and retention requirement
Production publication must document participant consent, recording notices and data retention behaviour.
08 / Business value
Expected operational value
1Projected
Less manual note taking and review effort
Automated transcription and summarisation reduce repeated manual note preparation.
2Projected
Clearer action items and decisions
Structured summaries make decisions, action items and follow up responsibilities easier to review.
3Projected
Searchable meeting context
Conversational search gives users a way to retrieve context from previous meetings.
4Projected
Automated reports and summaries
Reports convert captured discussions into reusable records for teams and clients.
5Projected
More consistent follow up after meetings
A connected workflow supports more consistent follow up after meetings.
09 / Technology
Every component, with its role in the delivery.
Technology choices from the supplied project brief, mapped to the workflow each component supports.
Angular
Web application interface
FastAPI
Backend APIs and workflow orchestration
MongoDB
Document and application data storage
Docker
Containerised deployment
JWT
Token based authentication
Related work
Explore related case studies.
