Your liquid cooling loop is a flow assurance problem.
AI racks now exceed 100 kW. The coolant network keeping them alive is designed with steady-state spreadsheets, while the failures that matter are transient. ignzai brings 30 years of oil and gas flow assurance physics to the white space.
The physics changed. The design methods didn't.
Racks outgrew air
100 kW+ accelerators made direct-to-chip liquid the default for new AI capacity.
Seconds of margin
A pump trip or valve slam can cook a GPU hall faster than any operator can react.
Steady-state guesswork
Vendor curves and spreadsheets can't see maldistribution, two-phase instability, or waterhammer.
Design, predict, protect.
Design
Verify before you build
Verify cooling networks against pump trips, valve closures, load steps and N+1 failures before construction.
Predict
A live digital twin
Neural surrogate models deliver real-time digital twins of the loop, thousands of nodes, live.
Protect
Catch it before it cascades
Early warning on operating data: maldistribution, incipient cavitation, thermal runaway precursors.
Network-level transient simulation, not room-level CFD.
Built on 8 years of transient multiphase flow assurance for ADNOC, Aramco and Borouge-scale projects.
Latest insights
View all articles →August 5, 2026 · 6 min read
Liquid cooling vs. immersion cooling: two different transient problems
Direct-to-chip and immersion solve the same heat problem with different network topologies, and different failure modes.
Read article →August 4, 2026 · 5 min read
Air cooling vs. liquid cooling: where the limit actually is
Air didn't get worse at cooling chips. Rack power got past what air was ever going to handle.
Read article →July 20, 2026 · 7 min read
Two-phase cooling: lessons from 8 years of multiphase pipelines
The instabilities showing up in two-phase liquid cooling loops have a name in the oil and gas world.
Read article →