Matic is a pretty amazing robot. It also happens to clean your house. Point at a coffee spill on the kitchen floor, say “Hey Matic, clean this,” and the robot turns to look at you – physically pivoting toward your voice, the way a pet or person might — and sees what you’re pointing at, motors over, and cleans.

You don’t need an app, a pre-mapped home space, or pre-labeled rooms.

But it also, despite the company calling it the “most American” robot available, doesn’t yet pass recent FCC rules about foreign robots .

Matic Cues is the update the Mountain View company pushed out last week to every Matic already in a customer’s home. The software upgrade makes it the first home robot that understands more than 70 spoken languages and universal human gestures, the company says.

Matic carries five cameras and a four-microphone listening array. The wake word – think “Hey Siri” or “Alexa” – runs entirely on the device, so ambient room audio never leaves the robot. Because it has a mic array, Matic can locate which direction your voice came from. Proprietary on-device software then finds you, sees your hand and your finger and even your eyes, then triangulates the target you’re point to against it’s own position in your house. Camera data never leaves the machine, and the microphones ship off by default, the company says.

Of course, on-device compute for a little robot vacuum doesn’t actually speak 70 languages: the actual command you say after the wake word is anonymized and sent to Google’s Gemini AI engine.

But will Matic pass the FCC foreign content ban?

On July 28, the FCC added foreign-produced "advanced robotic devices" to its Covered List, tech it says poses an unacceptable national security risk. The definition is wide enough to include most robot vacuums and robot lawn mowers: over 4.4 pounds, wireless connectivity above 200 kbps, environmental sensors, autonomous navigation. Devices that have already been authorized do keep their authorization and can keep selling, though the Commission layered on restrictions around firmware updates .

New models face a much harder path in, but there's a domestic-end-product exemption at 65% U.S. content by value, rising to 70% in 2029.

Which is where Matic’s position gets a little complicated.

Matic designs and assembles its products in California and markets itself as the most American robot in its category, but it does not currently clear that 65% bar.

"We’re the most American robot in the market, but we still have work to do in meeting the guidelines set by USG," co-founder Mehul Nariyawala told me via email. And, on whether the FCC action is a windfall: "Candidly, we have no idea how the FCC move will play out."

I recently ask him how Matic works, and what the FCC decision means for Matic, as well as other similar products.

John Koetsier: How does Matic understand pointing?

Nariyawala: Matic has 5 RGB cameras and 4 Microphones. When users say "hey Matic", it uses 4 microphone array to determine the direction of the audio and turns towards the users. This is critical as when we call another human or even pet, they look at us. This is the same. Matic looks at the users using its cameras. First it finds users, then it looks for their hand, then the finger, then eyes, and then it triangulates what users are pointing towards with its own position. It's a proprietary algorithm that we've trained that works entirely on device.

John Koetsier: Are all 70+ languages processed on-device?

Nariyawala: Yes. "Hey Matic" is all on device so nothing is going to cloud in terms of ambient sounds. The gestures are all detected on the device as well. No camera data ever leaves your robot. Once you say, hey matic, and you hear a chime, you can give a command. This command uses Gemini API to parse it anonymously. No user info is sent. We chose to do it this way because it enables 70+ languages and many commands. Once we get an understanding of the top commands used, we will distill a smaller on-device model for those who do not want to use Gemini API. In the meantime, if you don't want to use Matic Cues, you can turn it off in the settings. And microphones will remain turned off.

John Koetsier: What LLM are you using? On-board? What kind of CPU/GPU drives that?

Nariyawala: For "hey Matic" we've built our own model. To parse the commands in different languages, we use Gemini API.

John Koetsier: How well does it handle kids, accents, and noise?

Nariyawala: In our tests, it has worked very well across the board. Essentially, same performance as the Gemini. This was critical to us as we knew that many families are multilingual and have accents of their own.

John Koetsier: Is this a step toward a general-purpose home robot?

Nariyawala: It's a step towards Rosie the Robot. We want to put Rosie the Robot/Alfred from Batman in every home. However, our approach is different.

Most of what is being built in robotics today is technology looking for a problem to solve. Humanoids. Foundation models. World models. They are extraordinary feats of engineering — we mean that sincerely. But they are not products. They are technology built upside down, without a clear answer to the most important question for an iconic product: what problem do real families have today, and do these solve it?

Families do not want robots. They want self-cleaning homes. They want organized homes. They want to stop thinking about chores completely. Physical AI and robots are just the means to that end.

And, families are not guinea pigs. Their homes are not training sets. Privacy is not a feature. It is a right, so from day one, our goal has been to build a fully autonomous "unsupervised" robot that just works. And instead of starting with a human form factor, we’re following the sequence that Nature has proven. Nature does not build fully functioning humans. It grows them … slowly, in the physical world, through direct experience and self-reinforcement learning … in a precise order that cannot be reordered.

  1. First: perception. A child spends years simply learning to see and move through the world. She learns depth, objects, surfaces, obstacles, motion. That foundation must be solid before anything else is possible. They learn to navigate their homes, map their homes, localize themselves on that home during the first 5 years. They learn not to step into spaghetti spills or dog poop, learn to be careful around stairs, learn to not get tangled up with wires or strings, and learn not to bump into furniture. We’re teaching the same thing to Matic in the context of floor cleaning. This is an important step as self-driving car robots rely on google maps to know where the road is going and GPS to know where they are located on that road, but how does an indoor robot know if it's on the right side of your couch or left. That's the problem we solved first! We're the only team in the world to have five 9s of accuracy in SLAM (Simultaneous Location and Mapping).
  2. Second: manipulation. With the physical world of home understood, the child begins to master their hands. To pick things up, organize them, follow instructions, complete tasks. Reliable, purposeful action.
  3. Third: long-horizon planning. The ability to take on complex, open-ended problems. To make judgment calls. To handle the unexpected without being taught exactly what to do.

We are growing Matic through exactly this sequence. Deploying a trusted presence in the home, one phase at a time: 1) trusted floor cleaner, 2) trusted organizer, and 3) trusted housekeeper while solving real problems for real families in real lived-in homes with its chaos of kids, pets, toys, legos, wires, and umpteenth other things on the floor, everywhere.

John Koetsier: How important is on-device AI to your advantage?

Nariyawala: We have always believed that if customers win, we win. On-device AI enables customers to bring home robots that will be private, low-latency, and even affordable… it won't cost $20K or $500/month to pay for cloud bills. We believe this matters to customers and families. As fathers, we felt that families shouldn't have to jeopardize their privacy to just have their homes cleaned. So as long as customers value and demand this, it will remain an advantage for us. And, ultimately, they make a choice with their wallets… so far, we're fortunate that they are making that choice with Matic.

John Koetsier: Does being U.S.-made make you effectively immune to the FCC restrictions?

Nariyawala: Prior to Matic, we were at Nest. Mehul was a product lead for Nest Cameras and Navneet was a perception and computer vision lead. We learned first hand how much privacy mattered to consumers, and how much they disliked cloud-enabled cameras in their homes.

Hence, from day 1, we made a decision to build a robot that was private and secure by design. This meant that we had to design, assemble, and build as much of it as possible in the USA. At the moment, we design and assemble in the USA, but do not meet the FCC requirement of 65% components sourced in the USA.

We're the most American robot in the market, but we still have work to do in meeting the guidelines set by USG, and we're excited to meet those requirements as it is the step in the right direction for American families.

John Koetsier: Will the FCC move materially help Matic?

Nariyawala: Candidly, we have no idea how the FCC move will play out. However, if we build products that customers love, it will materially help us. If we preserve families' privacy and security, it will help us. If the FCC move increases the customer awareness of privacy/security lapses of many of these robots, then it will help us.

Look, Apple & Tesla compete worldwide, including in China. They are showing us that worldwide customers choose products they love. That's our focus. We simply want to build products that families love and that serve families needs.

John Koetsier: What physical capabilities come next? Form factors?

Nariyawala: We are moving in the direction of a "trusted organizer" phase. But we always start with a problem and work backwards, so for us, it's a function of what's the problem that customers' want us to solve next. That's what will determine the form factor and physical capabilities. All kinds of manipulation do not need hands, and we will show what we mean by that in the next few months (!).

John Koetsier: Thank you for your time.