Interact
End of session. You asked your twenty-five participants for structured feedback, and rightly so: that is where the real information about what worked is hiding. But now you are facing twenty-five free-text answers, a train to catch, and the next session to prepare. This is exactly where AI becomes useful — under one non-negotiable condition: your participants' words must not travel to a third party.
End-of-session feedback: precious, but slow to read
Good end-of-session feedback is worth gold. That is where a participant tells you the morning module went too fast, where another asks for more hands-on cases, where a third finally understood a concept that had been resisting them. These signals almost never surface out loud: public speech smooths everything over. Free text says what people actually think.
The problem is not collecting this feedback — SnapInteract’s structured feedback activity handles it at the end of the session, as we describe in closing a training session well. The problem is reading it. Twenty-five answers per question, several questions, several sessions a week: careful reading becomes a job in itself. And feedback you never read is useless. Many trainers end up skimming — or worse, they stop asking for feedback altogether.
What the summary does: trends, at a glance
SnapInteract offers an automatic summary of this feedback. Concretely: instead of a pile of answers to scroll through, you get an overall reading — the trends that stand out, the points that keep coming back, the general tone. What used to take twenty minutes of careful reading can now be taken in within moments, between two rooms or on the train home.
- Salient points emerge: what several participants say in different words gets brought together.
- Weak signals no longer drown in the pile: an isolated but relevant remark stays visible in the detailed answers.
- The overall reading arrives when it is useful: right after the session, while you can still adjust what comes next.
- Individual answers remain available: the summary is an entry point, not a replacement.
The central point: this AI works on-device, on your Mac
Here is the choice that sets this feature apart, and the reason this article exists. The feedback summary uses Apple Intelligence, on-device, on Apple Silicon Macs (with a recent macOS). The model runs on your machine’s chip. Nothing is sent to an external service: no calls to a remote AI API, no transfer of answers to a server for processing, no account to create with an AI provider.
Why does this matter so much? Because training feedback is sensitive text. A participant who writes that they understood nothing in module 2, or that the pace put them in difficulty, is confiding in you. They do it because the setting invites it — often under anonymity. Sending these confidences to a third-party AI service to be summarized betrays that setting, however good the intentions. And in many organizations — companies, higher education, the public sector — it is also, very concretely, forbidden or subject to approval.
Useful AI is not just AI that summarizes well. It is AI you can trust with your participants' words without having to ask anyone for permission.
This choice fits SnapInteract’s overall architecture: your courses, sessions and participant answers live in a file on your Mac, not on our servers. The AI summary follows the same logic — we detail this philosophy in your data stays on your Mac.
And without AI? The simple recap is always there
Let us be precise, because precision is owed here: the Apple Intelligence summary requires an Apple Silicon Mac and a recent macOS. If your machine does not tick those boxes, or if you prefer not to enable AI, SnapInteract always gives you a simple recap of the feedback: answers organized, readable, usable. You lose neither the collection feature nor the structured reading — you only lose the automatic summary. AI is an accelerator, not a dependency.
That is a design principle we apply everywhere: no essential feature should rest on an optional component. Your participants’ feedback is too important to be conditioned on a hardware generation.
What it changes in your week
The practical effect is simple: you can finally ask for feedback systematically. When reading cost twenty minutes per session, structured feedback was reserved for the important trainings. When reading costs two minutes, it becomes an end-of-session reflex — right alongside the session statistics recap. And regularity is what makes feedback truly useful: comparing trends from one session to the next is how you find out whether your adjustment to module 2 paid off.
There is also a posture benefit. Telling your participants that their feedback is analyzed on your own computer and travels nowhere changes the quality of what they write. The honesty of feedback is proportional to trust in the setup. On-device processing can be stated in one sentence — and the room hears it.
AI in service of the classroom, not the other way round
We do not believe in showpiece AI for training. We believe in the precise places where it removes a real chore without taking anything away from the pedagogical relationship. Reading dozens of free-text answers is exactly that place: repetitive, time-consuming work that the model does well, whose result gives you time back for what only you can do — adjust the next session. All of it on your machine, with your data, under your control. That is our definition of useful AI.
Frequently asked questions
Do I need a subscription to an AI service to use the summary?
No. The summary uses Apple Intelligence, on-device on Apple Silicon Macs with a recent macOS. There is no account to create with any AI provider and nothing is sent to an external service.
What happens if my Mac is not compatible?
You still get a simple recap of the feedback: collected answers remain organized and readable. Only the automatic AI summary requires an Apple Silicon Mac and a recent macOS.
Are my participants' answers sent anywhere for analysis?
No. Processing happens on-device, on your Mac. Answers live in a file on your machine, and the summary involves no transfer to any analysis server.
Does the summary replace reading individual answers?
No, it is the entry point: it surfaces trends at a glance, and you keep access to every detailed answer whenever a point deserves a closer look.
