Project
Meetings Manager
A multimodal workflow that turns raw meeting inputs into structured records, linked entities, and follow-up actions.
Project snapshot
- Industry
- Business operations
- Input modalities
- VoiceTextCameraFiles
Problem
The workflow challenge
Meeting information was being captured, but teams still needed manual effort to turn notes, recordings, and supporting files into usable records and next steps.
AI system built
What got implemented
Rel-AI-able built a capture-to-record-to-follow-up workflow that structures meeting inputs, links entities, and suggests actions.
Outcome summary
What changed after delivery
- Converted raw notes into structured records.
- Identified entities and follow-up actions.
- Supported capture-to-record-to-follow-up workflows.
Architecture notes
Delivery shape
- Voice, text, camera, and file inputs.
- Entity linking.
- Action management.
Problem context
A fuller look at the operational context, workflow inputs, and business outcomes behind the build.
Problem context
Meetings generate useful information, but that information often stays fragmented across notes, recordings, files, and follow-up conversations. The workflow needed a more structured way to turn capture into action.
AI system built
Rel-AI-able implemented a Meetings Manager workflow that converts raw inputs into structured records. It identifies entities, links follow-up context, and supports action management after the meeting itself.
Inputs and workflow
- Inputs can come from voice, text, camera, and files.
- The workflow structures those inputs into usable records.
- Entities are identified and linked across the meeting context.
- Suggested follow-up actions support the next operational step.
Business outcomes
The workflow turned raw meeting inputs into structured records, identified entities, and suggested follow-up actions. It connected capture, record creation, and action management in one operational flow.
Connected capabilities