Turn sustainability into an operating variable.
Energy, water, and carbon shouldn’t live in a quarterly report. AquaWatt DC OS treats them as live inputs to every operating decision — measured continuously and verified against real outcomes.
What we monitor.
Electricity
Real-time power draw across the facility and IT load.
Potable water
Fresh water consumed by cooling systems.
Reclaimed water
Recycled and non-potable water use.
Carbon intensity
Emissions per unit of energy from the grid mix.
Renewable availability
On-site and grid renewable supply signals.
Heat reuse
Waste heat available for capture and reuse.
Workload resource intensity
Resources consumed per unit of useful compute.
The metrics that matter, defined.
AquaWatt tracks the industry-standard efficiency metrics so your teams and stakeholders share one language for performance.
Total facility energy divided by the energy delivered to IT equipment. Lower is better.
Liters of water used per kilowatt-hour of IT energy. Lower is better.
Total CO₂ emissions relative to IT energy consumed. Lower is better.
Accounts for energy reused outside the data center, such as captured heat.
A measurable lineage, not a claim.
Every sustainability number can be traced back through the decision that produced it, the approval that authorized it, and the actual measured result — not a modeled estimate.
Water is local. Water availability and stress vary by region and season. AquaWatt can weight water more heavily in water-stressed locations, so optimization reflects the constraints that actually apply to each facility.
Make sustainability measurable at your facility.
Join the pilot program and see how energy, water, and carbon become live operating variables.
Most platforms count litres. We ask which litres.
Water is the constraint the industry noticed late. Treating it as a single number hides the only distinction that matters to a regulator or a community — where the water came from, and how scarce it was there.
Every source classified separately
Consumption is tracked by origin, so reductions can be targeted at the sources that carry real environmental and regulatory weight.
Water Usage Effectiveness
WUE calculated against configurable reporting boundaries, so the figure matches the boundary your disclosures actually use.
Water-stress weighting
Regional water-stress information feeds the optimizer. A litre saved in a stressed basin is not treated as equal to a litre saved elsewhere.
Drought operating mode
A policy mode operators activate that re-weights the objective function toward potable-water reduction for the duration of a restriction.
Cooling-tower optimization
Cycles-of-concentration and blowdown strategies recommended within water-quality limits — never outside them.
Reclaimed-water opportunities
Identifies where non-potable sources can displace potable use, which is often the largest single water win available to a site.
Water and wastewater cost
Both sides of the bill are modelled, because discharge is frequently the more expensive half and the one most often ignored.
Chemistry is a hard constraint. Water optimization respects conductivity, chemistry, corrosion and equipment water-quality limits. Saving water at the cost of a cooling loop is not a saving — it is a deferred repair bill.
Describes planned water intelligence capabilities of AquaWatt DC OS. Several are scheduled for releases after the first, and none represent water reductions achieved at a customer facility.
A data centre is a grid participant, not just a load
Once a facility can forecast its own demand and shift work in time, it stops being a passive consumer of electricity. AquaWatt DC OS is designed to coordinate tariffs, peaks, storage and flexible workload so that energy strategy becomes an operational capability — and to treat the heat the facility rejects as a resource rather than a by-product.
Tariff optimisation
Decisions account for electricity rates and demand charges, not just kilowatt-hours. The cheapest hour to cool is rarely the coolest hour.
Peak-demand reduction
The platform recommends actions that shave forecast peak demand, the component of an energy bill that punishes a single bad fifteen minutes.
Renewable alignment
Flexible workloads are aligned with renewable-energy availability whenever it is operationally feasible to move them.
Grid emergency policy
Customers define in advance how the facility should behave during a grid emergency, so the response is a policy decision rather than an improvisation.
Battery dispatch
Approved battery charge and discharge schedules can be recommended or controlled, within the limits the operator sets.
Demand response
Participation in approved utility demand-response programmes turns operational flexibility into a revenue and relationship asset.
Microgrid coordination
Longer term, approved on-site generation, storage and critical loads can be coordinated as one system.
Heat-reuse intelligence
Most of the electricity a data centre draws leaves the building as low-grade heat. Turning that into something useful is a modelling problem before it is an engineering project.
How much usable heat is actually there
Before anyone draws a pipe on a site plan, the platform estimates the volume, temperature and consistency of available waste heat. Consistency matters as much as volume — an intermittent heat source is difficult to sell and difficult to build around.
Describes planned energy, grid-coordination and heat-reuse capability of AquaWatt DC OS. These functions depend on utility programmes, on-site equipment and local infrastructure that vary by site, and are delivered across releases rather than in the initial pilot build. No savings, revenue or payback figures shown here represent results at a customer facility.
A savings number is only worth the method behind it
Most efficiency claims fall apart under scrutiny because nobody agreed what “before” looked like. AquaWatt DC OS treats verification as a first-class part of the product, not a report written afterwards.
Establish the baseline
Configurable energy and water baselines are built from historical operation before any change is made. Without an agreed starting point, a savings number means nothing.
Normalise for reality
Baselines are adjusted for the variables that legitimately move consumption, so a cooler month or a quieter cluster is never mistaken for an optimisation win.
Attribute and compare
Savings are attributed to the specific optimisation action that produced them, then predicted results are compared against measured results — action by action, period by period.
Detect rebound
The platform looks for savings in one period that are quietly offset by higher consumption later. A gain that does not survive the following weeks is not a gain.
Publish with confidence
Every verified savings figure carries a confidence score and the methodology behind it, so reviewers can interrogate the number rather than take it on trust.
Translate into finance
Verified resource savings are converted into the financial terms decisions are actually made in.
Describes the planned measurement and verification methodology of AquaWatt DC OS. It does not represent savings achieved at any customer facility.