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OnPrem

Use case

Everyone has an AI note-taker in meetings now. Almost nobody has asked where the transcript goes.

AI meeting assistants have gone from novelty to default in about eighteen months. Otter, Fireflies, Read, Fathom, Grain, plus meeting-app native ones from Zoom, Teams and Google Meet. Almost every professional we speak with has at least one running by default, and almost none can describe with certainty where the transcript, audio and summary end up.

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What the work looks like today

Before AI

Someone joins a bot into every meeting from a personal account, transcripts and summaries flow to their email, and the material stays there indefinitely. The bot has heard the client's private business, the internal reactions, the numbers discussed after the client hung up. That transcript is now a searchable, exportable record on a third-party service, tied to the note-taker's personal account, over which the firm has zero control.

The shortcut everybody's already taking

With a public chatbot

A well-configured enterprise tenancy of one of the major products is a genuine improvement. It still means audio and text of confidential meetings routing to and being retained on that service, and it still leaves the personal-account gap — the free version is one Chrome extension away for anyone who prefers it.

Same job, done properly

The on-premise version

A private note-taking system runs on your on-premise AI infrastructure. Audio can be captured locally (or via a captured room recording), transcribed locally, summarised locally, and stored where you already store other client-facing material. The productivity gain is intact and the transcript never leaves the building.

Where it lands

Concrete applications

01

Client meetings and file notes

The most obvious use — turning a 45-minute client meeting into a structured file note automatically. Also the most obvious confidentiality problem when the note-taker is a cloud service.

02

Internal partner and strategy meetings

Internal candour matters. Partners speak differently when they trust the room. A visible bot from a personal account changes the room, and staff self-censor accordingly. A private on-premise capture removes the "who's reading this" hesitation.

03

Board and investment committee meetings

Sensitive commercial detail, sometimes with market-moving implications. Recording obligations vary but the confidentiality obligations do not — and third-party bots have no place in most of these rooms.

04

Medical case conferences and MDT meetings

Discussion of identifiable patients, sometimes multiple. Health information under the Privacy Act. Cloud transcription services do not fit here without careful vendor assessment; on-premise sidesteps the assessment.

05

HR and workplace investigations

The category where confidentiality expectations are strictest and the potential for cloud-service data appearing in later disputes is highest. Do not use cloud AI note-takers for these meetings.

Meeting notes & transcripts: common questions

Can we still use Otter or Fireflies for external client meetings?
You can — the question is whether you should have documented consent and a documented data-handling assessment for each meeting where you do. Even the best-configured commercial product involves audio and transcript flowing to a third-party service, and clients rarely realise their meeting is being captured this way. On-premise is the option where the answer stops being "carefully" and starts being "safely by default".
Does this work with Zoom and Teams meetings?
Yes — the audio can be captured either via a local bot joining the meeting on your network, or via a captured recording processed after the fact. Which we recommend depends on your existing meeting environment; both are workable.

No obligation

Interested in meeting notes & transcripts specifically?

Tell us the volume and the sensitivity, and we'll tell you honestly what an on-premise setup would look like for this particular workload.

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