Follow-up work per person
Summarise, note tasks, distribute. Everyone does it for themselves – the same work, several times over.
Writing minutes, assigning tasks, then looking up three weeks later what was actually decided. Meeting AI takes that off your desk – locally on your own hardware, with a quote and timecode for every critical statement. No cloud detour, not even “just for the transcription”.
Local processing · No statement without evidence · Human approval
“We are moving the rollout to Q4 and taking the budget from the training pot.”
Task: adjust the budget plan
Owner: Speaker_1 · due 12 Aug
Ten to twenty minutes of follow-up work per participant per meeting sounds harmless until you scale it up. For a team of ten that quickly becomes 36 to 72 hours a month that produce no visible result.
Summarise, note tasks, distribute. Everyone does it for themselves – the same work, several times over.
Sometimes detailed, sometimes three bullet points, sometimes nothing. “What did we decide?” stays a question of memory.
Decisions live in emails, private notes and people’s heads. Before an audit, the hunt begins.
Where patient data, client information or internals are involved, the usual recorders are out – and minutes are still written by hand.
Use your own numbers instead of industry averages. Every assumption is disclosed and adjustable – including the cost side.
Including employer costs – set it conservatively.
Operations, LLMOps and energy for a local AI appliance.
Pilot project including hardware, reviews and buffer.
One person in one meeting for one hour = one participant-hour.
Operational break-even: from roughly 8.0 minutes saved per participant-hour, running costs are covered.
These numbers are assumptions. Your meetings are the proof: the Fast-Track tests it in 14 days with five real recordings – locally, without cloud.
See the Fast-TrackCalculation: participant-hours × (minutes saved ÷ 60) × hourly rate − running costs. Month = avg. 4.33 weeks. Time saved is counted once only, not additionally as “fewer staff”.
Every tool can summarise by now. The question is whether you can trust the result without listening to the recording again. Three things make that possible:
Every critical statement comes with the original quote, a timecode and a speaker label. If no evidence is found, the output says “unknown” instead of a plausible-sounding invention.
A second model checks the result against the transcript. Uncertain minutes go to review, poor recordings are blocked rather than answered confidently and wrongly.
No minutes leave the system without a check by the responsible person. Who approved what and when is in the audit log.
Speaker separation is privacy-friendly: the system only distinguishes Speaker_1, Speaker_2 and so on – it does not identify people. You assign names yourself afterwards if you want to.
Instead of a sales pitch you get proof: five real recordings from your everyday work, processed on a machine inside your building – either on an existing Apple Silicon Mac or on a loan appliance that I bring and take away again.
net, including setup, processing, reference comparison, report and results session. No travel cost surprises, no add-ons.
If you commission the full pilot project within 60 days, the €4,900 is credited in full. The Fast-Track then becomes its first phase in hindsight – not an additional cost block. Your worst case: five professional sets of minutes, an honest quality report and clarity.
Three short details – I will reply within 24 hours with a proposed date for the setup call.
Remote setup call, 30 minutes: we agree which five meetings are suitable – realistic content, no sensitive individual cases. You get the consent template and record as usual.
I process the recordings locally, write manual reference minutes for two meetings under the four-eyes principle and measure the AI results against them.
One single session, 45 minutes: results, numbers, recommendation. Then you decide – without a carousel of follow-up calls. It would be odd if a meeting offer needed five meetings.
These limitations are stated on purpose. An offer that fits everyone would be a sales trick.
Yes – and it is easier than expected. You receive a ready-made template with a recording notice and documented consent. For the test we deliberately pick meetings without sensitive individual cases. Depending on company size, the works council must also be involved.
No. Speaker separation only distinguishes Speaker_1, Speaker_2 and so on, without biometric person recognition. You map names yourself if you need them.
On a machine inside your building – either your own Apple Silicon Mac or a loan appliance. There is no cloud detour, not even for transcription. After the project the test data is verifiably deleted within an agreed period.
Then the report says so – with measurements instead of excuses. Results are compared against manually written reference minutes. If your room acoustics or dialect push transcription to its limits, you learn that in a €4,900 Fast-Track rather than later in a project costing many times more.
For the Fast-Track, barely – one setup session is enough. Your IT team is welcome to watch: the setup is built to survive an audit, with network segmentation, disk encryption and role-based access.
If the result is positive, an eight-week pilot with your team, clear metrics and a basis for the rollout decision. The €4,900 is credited in full. If the result is negative, nothing follows – you keep the report and the minutes.
You have five meetings this week anyway. The only question is whether someone will write the minutes by hand afterwards – or whether those five meetings become the proof.
Note: The figures in the calculator are model calculations based on typical values and do not replace a proper business review. Statements on recording, consent and retention are general orientation and do not replace individual legal or data protection advice – involve your data protection officer and, where applicable, the works council. As of: July 2026.