All use cases

Engage / Lifecycle

Morning sleep-recap and day-plan

The first thing your user sees on waking is last night's sleep turned into a plan for the day ahead, not just a number on a dial.

Get aheadSystem triggerTime-based triggerPushIn-appChatWellness (B2C apps)

What it does

A sleep app scores the night and then leaves the user to interpret it. A raw score is a verdict, not a plan, so the user glances at it and closes the app — and an app that is only opened to dismiss a number is an app on its way to being deleted. On wake, the agent reads the finalized sleep score and stages and turns them into a short recap plus a forward energy plan tied to the day: when the dip is likely, when to schedule focus work, when to move. It makes the morning open a ritual the user comes back for, because the data now tells them what to do, not just how they did.

How it works

  1. 1
    Trigger. the night's sleep session is scored and finalized on wake — a sleep_scored event from the device or app backend, gated to the user's usual wake window.
  2. 2
    Decision. the agent reads the score, stages, and the user's recent baseline from memory, then drafts a recap and an energy-curve plan keyed to that profile; every unprompted message clears a quality judge for tone and accuracy before it sends.
  3. 3
    Action. a morning push lands the one-line recap and the day plan, tappable into chat where the user can ask why a night scored the way it did or how to set the day up.
  4. 4
    Follow-through. what was sent and how the user engaged writes back to memory so tomorrow's recap reflects the trend, not an isolated night; if the user already opened the app and saw the score, the queued push is cancelled so it never duplicates.
Example
AgentMorning. You slept 6h10 last night, a bit short of your usual, with light deep sleep. Expect an energy dip around 2pm. Do your hardest focus work this morning while you're sharp, and keep the afternoon lighter. Want a wind-down reminder set for tonight?
CustomerWhy was deep sleep low? I went to bed early.
AgentEarly to bed helps, but your sleep didn't settle until a while after lights-out, which trims deep sleep. A darker, cooler room and screens down earlier tend to move that. I'll nudge you at your wind-down window tonight.

Configuration

How the agent is wired for this use case.

Triggera sleep_scored event from the wearable/device feed or app backend when the night finalizes on wake, gated to the user's wake window.
Tools & actions
  • Wearable/device feed · reads the finalized sleep score, stages, and wake time for the night.
  • Memory store · reads the user's recent sleep baseline and recap history; writes each recap and response back for trend continuity.
  • Knowledge base · retrieves sleep-science-grounded recap and energy-curve guidance to shape the day plan.
  • Messaging channel · sends the morning recap push and answers follow-up questions in chat.
  • Scheduling system · queues the recap and cancels it if the user already opened the score, and sets an optional wind-down reminder.
Autonomythe recap and day plan render unattended only after a quality judge clears each output; the agent gives general sleep-hygiene and energy-planning guidance and never diagnoses a sleep disorder or interprets the score as a medical finding.
Channelspush · in-app · chat
Escalationa pattern that reads as a possible sleep disorder, or a user message describing a health concern, hands off to a human or the app's clinical-resource path rather than being coached.

What you need

The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.

Signals

a finalized sleep_scored event per night with stages and wake time, plus the user's typical wake window.

Data

the user's recent sleep baseline and trend, recap and response history in memory, notification preferences and consent.

Guardrails

judge review on every recap; a hard boundary that the recap is wellness guidance, not a clinical or diagnostic read of the score; quiet hours and a once-per-morning cap; possible-disorder patterns route to a human.

Metrics it moves

  • dau-mauup, a recap that plans the day gives the user a reason to open the app every morning, not just on a bad night.
  • open-rateup, a recap pegged to last night's real data is more openable than a static score notification.
  • session-lengthup, the tap-into-chat path turns a glance into a short conversation about the day.
  • churndown, a daily ritual built on the user's own data is the habit that keeps a tracker installed.

Related use cases

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Recovery-score readiness coach

the fitness-segment sibling on a recovery score rather than a sleep score

Retain / Save

Hardware-tied subscription renewal save

the same sleep data, pointed at saving the renewal

Engage / Lifecycle

Daily mood check-in companion

the same morning-ritual pattern in the mental-wellness segment

See it on your own customer journey

Bring one drop-off, one churn cliff, or one silent segment. We will show you what a proactive agent with memory and judgment does with it.

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