
CEO @structifyai. ex-@MaticRobots. Yale. đŚ Just a dude who likes ML
Brooklyn, New York
Joined November 2022
- Tweets1.4K
- Following822
- Followers1.3K
- Likes2.3K
Pinned Tweet
We raised $4.1M for this moment: introducing Structify Flows.
It's the first âvibe data engineeringâ platform that lets you do enterprise-grade data work in minutes:
With Structify, just describe what you want in plain English.
No code. No hiring. No backlogs.
Alex Reichenbach retweeted
we made all of the functionality on mineflow free, only thing that costs $$ is downloading our data or uploading your own
Alex Reichenbach retweeted
Today weâre launching a mobile app that will make your next trip magical. â¨
Weâve helped 10,000s of travelers plan real trips, step-by-step. Weâve learned how AI can help you save time, money, and stress.
Weâve used that knowledge to build an assistant that goes on your trip with you. Take a look at what it can do:
After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order.
So we built Matic the way nature grows a child.
Finally, sharing our vision:
1.â â Why robots get stuck at the demo
2.â â Why labs can't ship robots
3.â â Why we started with eyes, not hands
4.â â The 99.999% rule in robotics
5.â â Where Matic is going next
1. Why most robots get stuck at demos
Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor.
A familyâs home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too.
Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos.
2. Why labs can't ship robots
SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem.
But real homes are the most chaotic spaces that exist.
There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around.
So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them?
Calling it âsolvedâ misses the question families actually care about: can I leave this thing alone and trust it?
3. Why we started with eyes, not hands
Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another.
Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected.
Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough.
Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it.
Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition.
Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores.
The floor cleaner isnât a detour from our larger ambition. It is how weâre building toward it.
4. The 99.999% rule in robotics
At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs.
Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home.
Matic's visual SLAM runs at 99.999% in 16K+ homes. Weâre the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went.
We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs.
Families control what leaves their homes. We do the work of making the product better.
Better robots earn trust > trust brings more homes > and more homes teach the robot more.
5. Where Matic is going next
Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes.
Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores.
Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution.
The goal isnât to put the most impressive humanoid in your living room.
Itâs giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility.
More time for each other. Less work getting in the way.
Thatâs Matic.
Get yours today at maticrobots.com
Alex Reichenbach retweeted
Introducing Cues: Voice & Gesture control for Matic
We raised $115M and spent 9 years to make the worldâs first intuitive home robot
Say you spilled coffee: Point to the spill and say, "Hey Matic, clean this" and it will hear, see, locate in 3D, and go clean on its own.
Matic comes with a lot of features:
1. Say "Hey Matic" - it locates your voice, turns, and looks at you
2. Say "Hey Matic, follow me" and start walking. Matic will follow behind
3. Say "Hey Matic, go clean the living room". Since it knows your house map, it navigates and just does it
It's so easy, a 5 year old and an 80 year old can use it and it understands 75 different languages.
Matic has 8x the airflow, specialised cleaning algorithms for rugs, corners, toekicks, mopping, etc and cleans better than any other robot vacuum.
Also keeps improving with software updates.
13,000 families use and love Matic.
WIRED magazine gave it a 10/10 (the only hardware to receive this rating in a decade)
Buy yours at maticrobots.com and if you don't love it after 6 months, we'll give you a full refund.
To celebrate our launch, we're cleaning 300 homes with Matic in San Francisco and New York City.
Comment "Matic" below, we'll send you the link to sign up and come to your doorstep to clean your home with Matic.
It took us 9 years, 11 prototypes, and our life savings to learn that every great product has the same design process.
Matic is now decisively the best home robot for families (I'm biased)
A 500-word thread and video on the Universal Design Process behind every great product:
Alex Reichenbach retweeted
This is a plan for Phase 2 of the National Security Renaissance: Project Alexander. It proposes a national security asset class to accelerate the effective and efficient deployment of capital into technologies vital to the nation's security. đşđ¸
Our Congress, Treasury Department, and private citizenry have the power today to enact critical reforms that will have an immediate and transformational impact on American innovation.
All feedback welcome! đ§ľ1/14
Palantir has kept these tools in an isolated, walled garden that price excludes the midmarket and refuses to allow the enterprise market to self manage.
If you want that era to end, try structify. DMs open.
âPointing an LLM at hundreds of disconnected, ungoverned databases gets you a system that hallucinates, is insecure, and unauditable. For something as consequential as our nationâs agricultural data, that is not just useless â itâs dangerous. The Ontology has been the key to delivering AI-enabled technology to every farmer in the country.â
At AIPCon 10, the USDA demonstrates how the Ontology now underpins national food supply security.
Alex Reichenbach retweeted
Letâs go Knicks đ
Great seeing @alexrkonrad @shensi @bernhardsson and @ryanjdaniels today.
General consensus: NYC > SF on all fronts
Great seeing @alexrkonrad @shensi @bernhardsson and @ryanjdaniels today.
General consensus: NYC > SF on all fronts
My favorite structify workflow. It pulls from all my outreach methods and my CRM, and lets me know who I need to reach out to by slacking it to me.
Very much agree with this. It is so easy to build a bad product now and still hard to build a good one.
People just have a temporary illusion that their internal teams will love using their badly built internal tools.
To be fair. Copilot responses do make me laugh
Copilot is âfor entertainment purposes only,â according to Microsoftâs terms of service techcrunch.com/2026/04/05/coâŚ
Weâre on it! We let the semantic layer get defined through chats. And a native claude plugin is in beta - feel free to dm.
This may be a dumb question but Iâll ask it here anyways:
I canât find a good way for my various AI chats to automatically sync its conversation history into a structured knowledge base. So that as I update various chats from time to time and refine context, my knowledge base automatically grows with this new info.
Itâs unfortunate but required. Vibe coding is a security risk that apple doesnât want.
Letâs stop vibe coding nonsense and actually figure out how to make AI work at work.
Apple's crackdown on vibe coding apps puts it on the wrong side of history
vibe coding is the biggest democratization of software since the App Store itself. But Apple is blocking the tools that make it possible.... the same week it turns 50.
The irony is that Apple should be leading this moment and instead its holding it back
w/ @jaswu_
Weâve been tackling this at Structify recently. Doing practical, responsible AI is both annoying and important. RBAC on every context node. Every data source needs different permissioning. Every query needs different permissioning.
It might be annoying, but if you donât do it, you have a countdown until your next data leak.
Very much agree. We still pay for Hubspot. I have no interest in trying to reinvent that wheel and find all the edge cases from scratch.
SaaS is dead.
Why pay $45/month when Claude Code can build you anything for $200/month?
Except there's an issue.....
Most people donât want to spend their evenings or work ours prompting AI, debugging edge cases, and figuring out why the payment process is broken again.
I'll die on this hill, but people have always paid for convenience.
They want to open an app and have it work.
The best apps look simple.
The backend is anything but.
That gap â between what users see and what actually runs underneath â is where all the work lives.
SaaS is dead. Of course, for those who want to engage in bait.























