AI compute and foundation models · United States
Compute for living and moving intelligence.
Sinewgrid builds GPU infrastructure and trains foundation models for two problems: how cells are programmed, and how machines learn to move. One cluster fabric serves both.
Pre-launch. Capacity, customers and certifications appear as placeholders until each one is verified.
Source: [executed power and site agreements]
Source: [signed letters of intent or contracts]
Source: [third-party cluster benchmark]
One compute fabric. Two model families.
Start with the approach, then follow either lane, or go straight to the platform and what we will and will not claim.
Why vertical compute
How a purpose-built stack differs from general GPU rental, and how closed loops tie models to experiments.
Read the approach → Sinewgrid CellCell and mRNA programming
Foundation models for how cells respond to sequence and perturbation, with a staged, lab-in-the-loop roadmap.
See Sinewgrid Cell → Sinewgrid MotionRobot learning
Models trained on simulation, teleoperation and real-robot data, built around a data pyramid.
See Sinewgrid Motion → PlatformThe compute stack
Racks, fabric, scheduling and storage as one stack, shown with a live scheduler view.
Explore the platform → TrustWhat we commit to
Six commitments, each paired with the evidence that has to exist before we claim it.
Read the commitments → CompanyThe team and the name
Where Sinewgrid comes from, who is building it, and who stands behind it.
About Sinewgrid →Planning a training run?
Tell us the model, the data and the schedule. We reply with a capacity plan and the evidence behind it.