Andrew Hart
@AndrewHart • 28,054 subscribers
Building robot brains at Base Intelligence 🤖🧠. Prev. Founder @ Hyper “Indoor Google Maps”, rolled out with IKEA. Pioneered AR navigation 🏳️🌈
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Today we signed a deal with a global retailer to roll out to every store. Good start to the week!
Andrew Hart10,863,448 views • 2 years ago
Craziest DM I ever received, from a VP at a global retailer: "Our app is shit and we know it's shit". I met her for coffee and she asked me if I could solve the biggest unsolved problem in retail. This is a deep dive into why and how Hyper built a 1m-accurate indoor GPS. This DM arrived in 2017. My outdoor AR navigation demos had just gone viral, and my new open-source project for Apple had elevated me to be the top trending iOS developer on GitHub. The retail exec told me they wanted to bring indoor maps and navigation to their retail stores, so customers could find what they’re looking for, and they could pop up relevant promotions along the way. It turns out that every office, university, events venue, hotel, airport, warehouse, factory — basically everywhere indoors have some need to navigate people around, provide relevant information, and improve efficiency. I assumed this was a solved problem. No. They do have maps on their app, but they aren’t able to navigate people because GPS doesn’t work indoors. They tried every solution out there to provide the blue dot, but nothing worked. I did know something about maps and location already — the first startup I worked at built an early version of Pokemon Go. I’d been tasked with generating the gamified maps, and populating the monsters and rewards. So I knew a bit about maps, coordinates and GPS — and monster training. But indoor navigation was new to me. Over the years, I’ve slowly become an expert in this, so let me explain. For indoor navigation to work well, the blue dot location needs to be 2x as accurate as a strong GPS signal. An aisle in a store is usually about 2 meters wide, so an accuracy wider than 2 meters would be fixing you in the wrong aisle. There are many research studies aimed at solving this, and Apple and Google have made acquisitions to help them in this area over the years. There were also many startups who claimed to have solutions, but when I spoke to their customers, I discovered that they weren’t happy with anything they’d tried: - Bluetooth beacons. Install thousands of these small sensors, which are a bit like AirTags, and use them for triangulation. But the bluetooth signals are noisy, making the location about 5 meters accurate, so it would jump you between multiple aisles in a store. Plus, lots of infrastructure to maintain. - WiFi. More promising than beacons, because every business has WiFi installed already. But the same radio signals problem means the location isn’t accurate enough. - Magnetomers, which use the earth’s magnetic field. This one sounded more promising. But it takes several minutes of walking around until it will give you a “blue dot”. So this was a bad user experience. - Computer Vision, which works like Google Street View. The user holds up their phone to scan the environment, it recognises their surroundings and locks them in. But this is clunky for the user, and they need to do this repeatedly every time they want a location update. Once again, bad user experience. Here’s an example of Apple’s own accuracy using WiFi. (I’ll show our own performance on these same sessions further down).
Andrew Hart2,798,970 views • 10 months ago
it’s crazy what happened with this ex-Apple employee in less than 6 months > September 2025: Apple asks designer Abidur Chowdhury to introduce iPhone Air. Notable for his very soft, kinda whimsical british accent. Jony Ive v2. > November 2025: Abidur leaves apple to join “a stealth startup”. Unprecedented for this to happen. Apple choose very carefully who to feature in keynotes, especially for such prominent announcements like a new iPhone design! They usually pick people who they expect to stay for decades, it’s a ladder into Apple leadership. > March 2026: Brett Adcock, founder of Figure robotics, announces his new startup, Hark, with a launch video featuring the soft british tones of… you guessed it! Only 6 months after introducing iPhone Air for Apple!
Andrew Hart361,582 views • 2 months ago
A few months ago, we decided to shut down Hyper. We built an amazing product and technology - better than I ever could have imagined - and rolled out with huge retailers like IKEA. But growth was impossible. 2-3 year sales cycles, in a challenging market. Hard product, hard distribution. It's been a crazy ride over six years. There are so many people to thank, and we have so many stories to tell -- some day. As for now, I'm feeling good. 2026 is the future. I'm going to take everything I've learnt about researching a breakthrough technology from first principles, and apply these lessons to something new. 🤖🤖🤖 I will talk more about that in the new year.
Andrew Hart133,554 views • 6 months ago
Hyper has developed the best indoor location technology in the world: 1m-accurate indoor GPS. But this is an enterprise game. To scale to a billion people, we’re actively exploring selling our tech to a larger org. Everything I’ve learnt building indoor location over 7 years 👇
Andrew Hart208,388 views • 10 months ago
Genuine customer reaction while testing in-store AR navigation 😂😍
Andrew Hart481,435 views • 2 years ago
Next year, Hyper will be VERY open. We’ll talk about our customers (BIG global retailers) and how our tech works. For now: - We can map a huge store with 50k products, in mins - We can locate a user with 1m accuracy - And navigate them with AR Lots to come, I’m excited.
Andrew Hart324,063 views • 2 years ago
Testing our AR location + navigation tech at a large US grocery store 😍
Andrew Hart292,444 views • 2 years ago
Once we started to work with large global retailers, we needed a better way to scale this process. Ideally, the staff at the store could do this themselves — rather than us flying our team across the world — and then we could lower the cost and timelines. So we built a self-serve version of our survey app, with a tutorial mode designed for beginners. Over time, we collected millions of data points, and so we were able to develop an algorithm which would auto-correct mistakes. In other words, if the surveyor accidentally placed their ground-truth location in the wrong place on the map, we could use our algorithms to detect it, and correct it. So now we have WiFi, and with and our efforts on producing a high quality survey, we have the best WiFi positioning available. With WiFi on its own, it’s achieving 3 meter accuracy. This is a great foundation to build on. WiFi + Motion data To refine this down to 1-meter accuracy, we realised that we could combine WiFi with the same technology behind self-driving cars and robotics: a motion system called SLAM (Simultaneous Localization and Mapping). SLAM uses the accelerometer, gyroscope and camera system to understand precise device motion. Imagine a car driving through a tunnel, using the motion since its last GPS ping to keep location accurate until it comes out the other side. On a phone, this technology is very reliable, and measures device motion with high precision. But SLAM is measuring motion within its own coordinate space, it’s not aligned with the real world. SLAM tracks the user’s relative motion, like “moved forward 2 meters, then turned left”, but does “forward” mean “north”, or some other direction? It’s not calibrated, so it could mean any location, any direction. We can’t rely on the compass to help us out with this, because phone compasses are notoriously incorrect — everyone knows the frustration of being sent the wrong way down a street. So our job was to align this motion data with the triangulation data we were receiving from WiFi. We designed an algorithm that could simulate every possibility, filter the unlikely scenarios, and hone in your location, using WiFi as an anchor. So WiFi gives us the initial blue dot, SLAM gives us motion, and as the user starts walking and we receive more data, our algorithms can refine location accuracy down to a consistent 1-meter accuracy. We’ve tested these algorithms in many locations, on hundreds of hours of ground-truth data:
Andrew Hart90,944 views • 10 months ago
Just added indoor navigation to WeWork, without them knowing. Got this up and running in 2 days, using wifi + motion data for precise location. Every other indoor solution takes months and usually require beacons. Hyper is going to fix the indoor navigation space. 💪
Andrew Hart90,276 views • 1 year ago
What I’ve learnt: Indoor maps/location has massive potential but has been stuck in enterprise hell for the past 10 years. Every solution is inaccurate, expensive, bad UX, impossibly slow to deploy. Hyper will radically transform this. Our first release has two innovations: - Self-serve onboarding == zero enterprise sales cycle - Hyper app == zero implementation, no code required With this, we've cut the sales + integration process from months to days. And of course, our technology is precise, affordable, scalable and great UX. The opportunity size here is huge -- from hospitals to airports, from museums to warehouses. I'm excited to keep pushing with new releases that make indoor location useful and accessible to everyone.
Andrew Hart13,885 views • 1 year ago
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