HoverHealth and Fitness Logger
An AI wellness agent that logs workouts, tracks habits, monitors patterns, and gives you the complete picture of your health over time — through conversation, not data entry forms.
The Problem
Fitness apps track data. Nobody tracks patterns.
You have a step counter on your phone. A workout app. Maybe a sleep tracker. Perhaps a food log you started in January and abandoned by February. Each one tracks one thing reasonably well. None of them talk to each other. And none of them tell you the thing you actually need to know: how your habits connect, what's working, and what's slipping.
The fitness tracking industry is obsessed with measurement and terrible at meaning. You can see that you slept 6.2 hours last night and walked 7,400 steps today. What you can't see is that every time your sleep drops below 7 hours for three consecutive nights, your workout intensity drops, you skip the gym more often, and your stress eating increases. That's a pattern, and no single-metric tracker will show it to you.
The other problem is logging friction. Opening an app, finding the right screen, entering sets and reps and weights — it takes longer than the rest period between exercises. Food logging is worse: weighing portions, searching databases, estimating serving sizes. The friction guarantees inconsistency, and inconsistent data is barely better than no data.
Hover solves both problems. It accepts input through natural conversation — "did chest and tris today, bench felt heavy, skipped the last set" — and structures it into proper logs. It connects data across domains — sleep, exercise, nutrition, mood, habits — and surfaces the patterns that single-domain trackers miss.
How It Works
Log naturally. Learn automatically.
Mike runs on a Haiku-class model — fast enough for quick logging interactions, lightweight enough to run frequently throughout the day.
Tell Mike what you did in natural language. "Ran 3 miles this morning, felt sluggish." "Had a salad for lunch, coffee at 3." "Slept terribly, woke up twice." Mike parses the information, structures it into the right categories, and logs it properly. No forms. No dropdown menus. Just conversation.
Mike tracks across domains: exercise (type, duration, intensity, perceived effort), nutrition (meals, hydration, supplements), sleep (duration, quality, disruptions), habits (meditation, reading, screen time), and subjective wellness (energy, mood, stress). All in one system. All cross-referenced.
Mike tracks the habits you're building (or breaking). It maintains streaks, notices when consistency drops, and alerts you early — not after you've already missed a week. "You've meditated 12 days in a row" is encouraging. "You usually run on Wednesdays but haven't in two weeks" is a gentle nudge before the habit dissolves.
This is where Mike differs from every fitness tracker. It looks across domains and finds correlations. Sleep quality affects workout performance. Caffeine timing affects sleep quality. Stress levels correlate with dietary choices. Mike surfaces these connections as natural-language observations: "Your workout intensity is consistently higher on days you sleep 7+ hours and skip afternoon coffee."
Each week, Mike generates a summary: what you did, what you skipped, how key metrics trended, and which patterns held or broke. The review is written for a human, not a data analyst. Concrete observations with context, not a spreadsheet dump.
The OS Underneath
Wellness infrastructure, not another app.
Mike runs on the Montebelle agent operating system — designed for persistent tracking with real continuity.
Memory Continuity
Mike maintains your complete wellness history across sessions. It remembers your baseline metrics, knows your personal records, tracks long-term trends, and understands your seasonal patterns. When you ask "am I stronger than I was six months ago?", Mike has a data-backed answer because it's been tracking the whole time.
Verification Gates
Mike never gives medical advice. It tracks data, spots patterns, and reports observations — but health claims are flagged as patterns, not diagnoses. Unusual data points (like a heart rate that seems too high or a sleep duration that seems implausible) are flagged for confirmation rather than silently logged. The agent is a tracker, not a doctor.
Fleet Learning
Pattern recognition techniques and logging accuracy improvements discovered across the Montebelle agent fleet feed back into Mike's processing. Better natural language parsing, more accurate exercise classification, and improved correlation detection — all shared across the network without sharing any individual's health data.
Ready to see what an agent looks like for your workflow?
Hover is one configuration of the Montebelle wellness agent. Your version tracks the domains you care about, through the channels you prefer, with the level of detail that fits your lifestyle.
Let's TalkFixed price. Two to four weeks. You own the agent.