Automations

Advanced  Reviewing every check-in by hand doesn’t scale. An automation reads a new progress entry and drafts the analysis for you — you stay the editor and approver; the AI just does the first pass.

Automations live in Vault → Automations. Today there’s one kind: the Progress Report. The whole loop looks like this:

Set one up

From Vault → Automations → Create automation, choose the Progress Report kind, then configure:

1 · Trigger. It fires when a client submits a new progress entry — and you can scope which entries count along up to four dimensions: specific forms, lifecycle stages, assigned trainers, and/or specific clients. Set as many as you like and combine them freely; leave a dimension empty (Any) to ignore it. Only check-ins that match every dimension you’ve set generate a report — so a “weekly check-in for active clients of Coach Mara” automation stays narrowly on-target and never fires on anything else. (An ordinary intake/survey submission doesn’t trigger it — only a progress entry does.)

More than one automation can match. If two active automations both match the same check-in, each one drafts its own report, and both show up on that entry. Scope them so they don’t overlap, or embrace it — switch between the reports on the entry (see Progress reports).

Only scheduled check-ins auto-run. To avoid noise and wasted analysis, the automation fires only when a client answers a scheduled check-in (a reminder / check-in to-do you set for them). A client’s free-form entry — or one you log for them — does not auto-draft a report. You can still draft one anytime: open the entry’s report panel and Generate with AI.

2 · Data fed to the AI. The heart of the analysis is this check-in plus the last few (0–5; the previous check-ins are what give the AI a trend to reason about). You can also fold in the client’s onboarding / initial-questionnaire answers, a client profile snapshot, and the most recent chat messages — each toggled on or off, and each genuinely included in what the AI reads when you turn it on.

3 · Sections the AI fills in. A report always has the same three parts (you can reword how each is written, but not add or remove them): a client-facing summary, internal notes, and a priority flag. (What each part is for — and how the client eventually sees the summary — is covered in Progress reports.)

4 · After drafting (post-actions). Up to five internal follow-ups — Notify trainer in app, Send email, Send WhatsApp, or Update a field on the entry (e.g. set its status). The pipeline never messages the client directly; those go out only after you approve.

5 · Save & activate. New automations save as a Draft. Hit Activate to make it live (you can Pause or Archive later). It only runs while active.

What it produces

Each run saves a draft report on the check-in — the client-facing summary, internal notes and priority shown above. From there it’s yours to edit, approve, discard or regenerate, exactly as if you’d written it by hand. The full anatomy of a report, the approval step, and what the client sees in their app all live in Progress reports.

You can also generate a draft on demand without waiting for a check-in: open any entry’s report panel and Generate with AI runs this same automation against that entry.

Run it & watch the runs

Once active, the automation runs itself on every matching check-in. You can also Run now… against a specific entry to test it. Each execution shows up in the automation’s run history:

Open a run to see exactly what data was sent to the AI and the raw result — handy when tuning a prompt. The Tokens column shows the real input / output token counts for each run, so you can see what each draft actually cost.

Examples

• Weekly reports for everyone. Pair a Weekly Progress Tracker form (set as your check-in form) with a Progress Report automation scoped to Forms → Weekly progress check-in (every other dimension left on Any). Every weekly submission now drafts a report.
• A different report per segment. Scope one automation to Lifecycle stage → Onboarding and another to Trainer → Mara, each with its own tone — and they’ll only fire on the clients they belong to.
• Catch the urgent ones. Keep the priority section on and add a Notify trainer in app post-action — you get pinged for review, and the Urgent badge surfaces the ones that need you first.
• Auto-file the routine ones. Add an Update field on progress entry post-action to set a status (e.g. Processing) so new reports land in the right column of your Progress inbox.

Automated reports vs. asking the AI

This automation runs on every check-in, the same way each time — a dependable first draft. For open-ended questions your dashboard never anticipated (“who’s drifting?”, “compare this quarter to last”), use the conversational AI agent instead. The automation is the routine; the agent is the ad-hoc.

That’s the engine that drafts your reports. For the report itself — editing, approval, and the client experience — see Progress reports. Back to the Forms & reports overview.