// robot-native ai compute
Data centers
that repair
themselves.
Reknit builds the robots and software that replace failed GPUs and whole racks with nobody in the hall. No human error, no waiting for a technician, and compute that can run anywhere.
↑ live simulation · click any server to break it · the robots will fix it
01 / vision
Compute anywhere.
No humans required.
When robots do the repairs, a data center no longer has to be built around people: no aisles to walk, no comfort cooling, no shifts, no mistakes. That changes where compute can live.
Robots do the repairs
Rail robots replace failed GPU trays and whole racks around the clock. No waiting for a shift, a ticket or a ladder: 3 a.m. is as fast as noon.
No human error, no human cost
Every swap follows the same steps: seated, connected, tested, logged. No one is in the hall near high voltage or coolant, and none of your budget goes to keeping a hall habitable.
More compute per acre
Robots don't need wide aisles, lighting or daylight. Halls get denser and go multi-storey, so cities and land-scarce regions can host serious compute.
Compute at sea, and beyond
Sealed, unmanned modules that never need a person to open them, cooled by the ocean and serviced by machines. Microsoft's sealed underwater data center (Project Natick) saw one-eighth the failure rate of its land twin.
02 / see it work
Want to see how a rack gets replaced?
A rack robot slides under the failed rack, releases its power, coolant and fiber, and swaps it for a spare from the dock.
- Fault detected, rack drained
- Rack robot drives under it
- Power, coolant & fiber release
- Failed rack carried to the dock
- Spare rack picked up
- Spare inserted & reconnected
- Back in service
And a single GPU?
An aisle crane pulls the failed GPU tray, drops it at the dock and slides a spare tray in its place. The rest of the rack keeps running.
- GPU fault, tray drained
- Crane lines up with the tray
- Tray unlatched & pulled
- Failed tray dropped at the dock
- Spare tray picked up
- Spare inserted, burn-in
- Back in service
03 / the problem
AI hardware breaks every few hours.
People can't keep up.
Every repair today waits on a person: someone to triage it, find the spare, walk the aisle, pull a heavy liquid-cooled tray and get every connector right. People are slow, expensive and scarce, and they make mistakes. And every hall has to be built around them, with wide aisles, comfort cooling, lighting and land.
04 / our promise
Uptime you can put in a contract.
Hours, not days
The swap starts the moment a fault is confirmed, day or night. We measure what your customers feel: drain to return-to-service, median and tail.
No human error
The same procedure every time. Every connector verified, every step logged, every part tested before it goes back into service.
Protect the SLA
Built for rack-level uptime commitments, so a single failed part doesn't turn into a service credit.
Every part accounted for
Full history for every serial: repeat offenders, bad lots, vendor turnaround, RMA recovery.
Safe by default
No people near high voltage, coolant or moving machines. A human approves every action until you choose otherwise.
Vendor-neutral
NVIDIA, AMD and every OEM in one system. No lock-in to a single hardware stack.
05 / why now
The hardware changed. Operations didn't.
- Rack-scale GPUs made the rack the unit of failure: one bad part idles far more compute.
- Liquid cooling and high-voltage power are making manual service slower, riskier and more specialised.
- Skilled data center technicians are hard to hire, and the build-out is outpacing them.
- Racks are becoming robot-ready, with cable-free, blind-mate trays that slide in and out.
06 / talk to us
Building or running AI compute? Let's talk.
We're working with a small number of GPU operators and new AI data center builds. Tell us about your fleet and we'll show you what a hall without people looks like.
support@reknitlabs.comFounded by engineers from Rubrik, Google and Atomic Vaults: we built self-healing storage; now we're building self-healing compute.