Data centers run better with
optimized cooling
and smarter maintenance.

Nexus DC helps operators cut thermal risk, reduce cooling waste, and plan service at the right time.

Demo: chip heatmap

Start with average temperature by rack. Then click a rack to open the chip-level heatmap for that rack.

Selected rack details (chips)
Selected
R2 (avg)
rack/chip
Now temp
current hour
ML +4h
model forecast
Airflow recommendation
increase airflow
The Problem

Thermal surprises hit the ops floor
before cooling can catch up.

A cooling & temperature story that repeats across data centers in 2025–2026 — not a spreadsheet, a shift handover.

Friday · 23:47 · Alert received

Duty engineer James sees hall averages in range — but rack A-14 inlet crept +4°C over 48h. The CDU was still on a static setpoint; chilled water couldn't follow the AI GPU load. The CDU trips. Cooling plant lags; a thermal cascade starts. Dashboards stayed green on coarse metrics.

MTTR: 4.2 hours. Revenue impact: $10M. Thermal stress on adjacent racks had been building for six weeks — invisible without per-rack temperature & cooling telemetry tied to operations.

⟶ The temperature story was in the data. Cooling policy wasn’t. Ops had no unified thermal + chiller view.
$2.4M
Thermal incidents = downtime $
When cooling can’t follow heat, incidents cascade. Average MTTR 4+ hours — often while operators still lack per-rack temperature forensics. SLA breaches, throttled GPUs, emergency plant runs.
↗ Gartner · Tier-3+ facilities · 2025–2026
40%
Cooling energy & setpoints
Chillers and CRACs follow fixed schedules while GPU load swings hour by hour. Without ML on temperature & plant data, operations over-cools “just in case” — burning power and masking hotspots.
↗ ASHRAE DC Energy Study · 2025–2026
Zero
Ops & maintenance blind spots
Work orders follow calendar rules, not thermal reality. No single view of rack temps, CDU health, and cooling plant margin — so operations teams chase alarms instead of preventing thermal debt.
↗ Operator interviews · CIS & EU · 2025–2026
Solution

Temperature, cooling & operations
— tied together.

Each row: what the ops & cooling team faces today → what Nexus DC automates with thermal + plant telemetry (2025–2026 deployments).

Today
Reactive ops — thermal incident after the rack is already out of spec
MTTR 4+ hrs · cooling plant playing catch-up · $2.4M/hr
With Nexus DC
ML on temps & components — ops sees thermal debt before SLA breach
RUL · inlet/outlet ΔT trends · cooling margin alerts −73%
Today
Static setpoints — same chilled water & airflow, every season, every hall
30–40% cooling kWh wasted vs dynamic heat-following policy
With Nexus DC
ML ties CRAC/CDU setpoints to live rack temps & load
Zone-level targets · chiller staging · ops-approved bounds −28%
Today
Operations runs on calendars — not on thermal or cooling plant health
Spreadsheets · fixed PM windows · no link between CDU wear and rack heat
With Nexus DC
One ops view: rack temps, cooling assets, prioritized work orders
Thermal heatmap · CDU/CRAC queue · Gantt by risk 100% coverage
Product

From temperature & cooling telemetry
to ops action in < 3 minutes.

01
Ingest
Temps · CRAC/CDU · BMS · Kafka
02
Predict
TimescaleDB · ML
03
Optimize
Cooling & setpoints
04
Act
Ops · CMMS · API

Three views from the Nexus DC dashboard.

Thermal Intelligence
Cooling & plant health
Operations planner

Thermal Intelligence

Inlet/outlet & delta-T per rack, hall vs rack gap detection, 72h temperature forecast. Built for operations: see where heat breaks SLA before the BMS alarm.

✓ Hotspot & ΔT visibility

Cooling & plant health

RUL and drift on CDUs, pumps, and heat exchangers correlated with rack temperature stress. Fleet risk score so ops fixes the chiller before racks throttle.

✓ Plant + thermal linked

Thermal what-if

Simulate chiller loss, airflow change, or load spike — see predicted rack temps and cooling margin before you change a setpoint on the live floor.

✓ What-if before change

Operations planner

Work orders ranked by thermal risk and cooling asset condition — Gantt for the ops team, handoffs to CMMS. Fewer unnecessary truck rolls, fewer missed thermal windows.

✓ Ops-ready schedule

Cooling, temperature & ops
in numbers.

Benchmarks and pilot data — 2025–2026.

$2.4M
Cost of 1 hour downtime
Gartner · Tier-3+ DC · 2025–2026
−28%
Cooling energy savings
200-rack pilot · cooling kWh · 2025–2026
−73%
Thermal-related downtime risk
RUL + temp models · 2025–2026
6 mo
Temperature & plant lead time
RUL · validated pilot · 2025–2026
Why Now

Three forces in 2025–2026
that overload temperature & cooling ops.

Higher kW per rack means smaller thermal margin — and higher cost when cooling lags even once.

Thermal density per m²
GPU and AI racks push 150–300 kW in the same footprint legacy gear used for 15 kW. Hot spots form faster; hall averages hide dangerous deltas at the rack face.
↑ 10–15× heat density vs 2025 baseline
🔄
24/7 cooling load
Inference runs flat-out. Chillers and CDUs see steady high thermal load — not the old batch peaks. Cooling plants must track minute-by-minute heat, not shift-level averages.
Sustained thermal load · 2025–2026 fleets
🏗️
New builds, green ops teams
Sovereign AI and regional capacity adds megawatts of white space — often staffed by teams that have never run high-density liquid + air cooling together. Temperature discipline and operations runbooks are the bottleneck.
Major DC capex wave · 2025–2026

Where Nexus DC sits in the stack

Thermal picture Rack and hall temperatures, ΔT, and BMS-class signals in one view—so “green” hall averages don’t hide inlet drift at the rack face.
Cooling in context CRAC/CDU, chilled plant, and setpoints read next to floor heat—not a siloed plant screen the shift forgets when an incident starts.
Built for operators Handoffs to O&M and CMMS: predictions show up as queueable work and runbook-friendly steps—not orphan analytics.

Cut maintenance spend and unplanned work by acting on thermal risk before it becomes an outage.

Teams using predictive thermal and cooling signals typically redirect a large share of O&M effort from firefighting to planned work — in pilots we have seen up to ~50% reduction in avoidable corrective maintenance and emergency plant runs when failures are anticipated rather than reacted to. Your mileage depends on fleet age and telemetry depth; we’ll quantify it on your data in a 15-minute session.

Nexus DC · 2025–2026 · by Unimatch

See how it works on your fleet data.

15-minute demo. No integration required. Bring a telemetry export and we’ll walk through live predictions on your racks — what we show, how models use your signals, and what ops would do next.