Meetings, hearings and sessions — transcribed where you decide
Recorded meetings are the most under-used information source most organizations own. The recording exists, the decisions are in it, and nobody can find anything in four hours of video.
What a meeting workflow produces
A transcript is the beginning, not the deliverable. From one recording a workflow can produce all of this in a single overnight pass:
- A timestamped transcript, searchable to the second
- Speaker segmentation, and identification against a known roster
- Caption files in the formats your video platform accepts
- A draft summary for a human to review and correct
- Topics, motions and named entities extracted
- Action items, where the meeting produced any
- An index entry, so the archive grows by itself
By the end of a year that archive answers questions nobody could previously ask: when did we last discuss this, and what was decided?
The deadline is the design
A meeting ends at nine in the evening. The transcript is needed by the morning. That is eleven hours of available compute time for perhaps twenty minutes of work — which means the job can run on a single modest machine, slowly, for free, overnight.
Live captioning during the meeting is a genuinely different requirement with genuinely different hardware. Some organizations need it. Many assume they do and, when asked directly, discover that nobody was ever going to read a caption in real time.
Ask when it is needed before asking what it runs on.
Public meeting, and the one that isn't
Same technology, different rules — decided by what is in the room, not by what is convenient.
- ingest recording Runs on your network
- transcribe overnight Runs on your network
- captions + summary Runs on your network
- publish to the public portal Runs on your network
- index growing archive Runs on your network
- ingest recording restricted share Runs on your network
- transcribe local engine only Runs on your network
- redact before anything is indexed Runs on your network
- restricted index permissions enforced Runs on your network
- Runs on your network Runs inside your own environment.
- Runs on managed Runs on infrastructure we operate for you.
- Runs on cloud Uses a commercial cloud or AI service.
Both run on the same hardware, in the same queue, using the same engine. What differs is where the output is allowed to go and who can search it — and that is enforced by the system rather than by everyone remembering which recording was which.
How quickly does the transcript actually need to be ready?
That one question changes the hardware, the cost, and often the whole architecture. It is a good place to start a transcription project.