June was about laying foundations. July was about seeing them pay off. The Korvi app landed on Android, we launched properly on social media, and our motion AI did something we’ve been chasing for the better part of 12 months: it watched a movement it had never been taught, and counted it.
Here’s the update.
Korvi Is Now on Android
The Korvi app went live on the Google Play Store this month, joining the App Store release earlier in the year. It’s out of testing and available to everyone.
That means the full Korvi experience (including AI-generated training plans, workout logging, a social feed, and progress tracking) is now a free download on whichever phone you carry. No paywall, no premium tier, no trial that quietly expires. If you train and you want a smarter way to track it, download Korvi and get going.
We also spent July making the app feel properly ours: a cleaner icon system, new exercise graphics (including female exercise illustrations, which too many fitness apps still skip), and a lot of unglamorous, but essential, bug-fixing behind the scenes.
Meet Your AI Coach
The feature we’re most excited about this month is a conversational AI coach built directly into the app.
Most workout apps hand you a rigid plan and leave you to it. Real training isn’t like that. You sleep badly or pick up a niggle. You go on holiday for a fortnight. Or, you feel unusually strong and want to push yourself. A plan that can’t absorb any of that isn’t a plan, it’s a spreadsheet with ambitions.
So we built something interactive. You can tell Korvi you’re feeling rough today and want the weights dropped. You can ask for something brutal because you’ve got energy to burn. You can cancel, reshuffle, or ask why a session looks the way it does. The plan updates around you, without derailing where you’re heading long-term.
Underneath, there’s a deliberate design decision worth explaining. The AI chooses your exercises; maths chooses your weights. Every load Korvi prescribes is calculated from your own logged performance using an estimated one-rep max, bounded within safe limits (see training engine blog). We’re not comfortable with a language model improvising how much weight goes on your back, and you shouldn’t be either. It’s a small distinction that matters a great deal when you’re the one under the bar.
Starting a session runs a quick readiness check on sleep and energy, and nudges the day’s targets accordingly. This may seem small, but it makes a real difference over months.
Our Sensors Learned to Recognise Movement On Their Own
This is the big one, and it deserves a bit of explaining.
Korvi’s wearable system uses five small IMU sensors placed around your joints, capturing motion data while you train. Turning that raw signal into something meaningful: a squat; a fourth rep; one rep that was slower than the last. This is the largest technical challenge that Korvi faces.
Until recently, teaching a model to do that meant labelling everything rep by hand. This is brutally slow work.
In July, we got our system working a different way. Rather than being told what each movement is, our models can now learn the structure of movement.
The practical result is genuinely fun to watch. You perform a movement once. The system records it. Then you just… train! Korvi recognises and counts each movement every time it happens, including movements it was never explicitly taught. This includes backward lunges and squat jumps, among others. It picks them up because it has learned what movement looks like, not just what a handful of exercises look like.
Crucially, our models are learning how to be invariant to normal human variation. Your reps aren’t identical. Some are faster, some are grindier. The lowering phase is often slower than the lift itself. A naive system comparing raw sensor readings falls apart the moment that happens. Ours doesn’t.
We also stripped out a large, computationally expensive component that the previous generation depended on for rep segmentation. It turned out we didn’t need it. The system is now considerably lighter, faster to train, and far more practical to eventually run on a phone.
Spotting Muscle Imbalances You Can’t Feel
One early finding stood out. While analysing squat data, our system flagged that one of our co-founders was consistently loading one leg less than the other, something he suspected from years of training, but which very few could have spotted by eye in the gym.
Left-right asymmetry is one of the most common and least visible problems in strength training. Most lifters have one dominant side. Most have no idea by how much, or whether it’s getting worse. It poses a genuine injury risk and can be a cap on progress. Until now, the only way to measure this properly has been a lab.
That’s exactly the kind of insight we’re building Korvi to surface: not a wall of joint angles and acceleration curves, but the handful of things that actually change how you train next week.
Designing Hardware That Can Actually Be Built
Less glamorous, equally important: this month we finalised the design for the next revision of our sensor hardware; v3.1.
The current generation works, but assembling each unit is slow, delicate, hand-soldered work. This is fine for a prototype, but impossible at any kind of scale, and a bottleneck on how fast we can collect data. The new revision is designed around a simple principle: zero soldering. Drop the board in, plug in the battery, plug in the charging connector, close the case. Every unit identical. It also leaves clean room to add features like haptic feedback later without redesigning the board.
We’ve also made a deliberate form-factor decision. The sensors will be flatter and wider rather than smaller and thicker. Anything that protrudes catches on clothing, gets knocked in a busy gym, and is simply less comfortable to wear. Comfort is not a secondary concern for a device you’re meant to forget you’re wearing.
Our boards are being ordered. More on this next month.
Growing the Community
Korvi is now properly live on social media. You’ll find us on Instagram, with TikTok following shortly, and we’re active over on r/Korvi and our Discord.
We’re not there to sell you anything. We’re a small team building an unusual product, and we’d rather show the process honestly than run adverts at you. Expect prototypes that look questionable, experiments that fail, and the occasional moment where the technology does something that makes us all shout at our phones.
Thanks for reading our blog too! Our deep dive on bar path tracking has become our most-read piece, and every post brings more lifters to the site, expanding our community. If there’s something about strength training technology you’d like explained properly, tell us and we’ll write it.
What’s Next
August is about three things:
- More data, more people. Our models are strong on the small group we’ve recorded so far. The next step is broadening that: more people, more body types, more training styles, all to make recognition robust for everyone, not just us.
- The next hardware revision. Getting boards ordered, assembled, and into the hands of the whole team so data collection can run in parallel rather than through one person.
- Turning insight into features. We now know we can extract things like rep segmentation and left-right symmetry. The work ahead is deciding what genuinely helps you train better, and building that into the app.
One year ago this was an idea about making strength training visible. This month Korvi counted our reps on its own. Thanks for following along.
Joe, Jake, Vish & Anisah
Korvi is a free AI workout tracker with adaptive training plans, social features, and a wearable strength training sensor system in development. Available now on the App Store and Google Play.