Capacity & rack management
Racks, circuits, space, power and cooling allocation in one live view per hall and per site. Reservations, move-add-change workflows and utilization reports driven by the same governed data.
Industries Data CentresData Centres.
Data Centres.
Uptime with
evidence behind it.
A data centre is a promise measured in uptime, power and cooling. The work happens between DCIM, BMS, meters and tickets, and every decision carries cost and risk. We build the platforms, AI support and digital twins that keep facilities efficient and the evidence clean, with your engineers making the calls that matter.
Why data centres are different
Every watt
is accounted for.
A data centre runs against commitments measured in nines, kilowatts and dirhams per kilowatt-hour. Power and cooling are the constraint on revenue, capacity decisions are capital decisions, and clients audit everything from alarms to access logs.
So the real product is not another dashboard. It is knowing how the facility actually behaves, testing changes before they touch live plant, and holding the evidence that proves the promise was kept.
What we build
From the plant room
to the client report.
Start with one hall, one system or one workflow. These are solution examples, not claims about previous deployments. Controls, review points and acceptance evidence are agreed before implementation.
DCIM & BMS integration
We connect to the systems you already run: DCIM platforms, BMS, SCADA, PDUs, CRAC and CRAH units, meters and environmental sensors, over the protocols and APIs your facility speaks. Your existing systems stay the system of record.
Energy & efficiency tooling
PUE and partial PUE measured and reported from meter data, with waste, drift and outliers made visible per hall, per system and per tenant load.
Incident, change & maintenance workflows
Faults, planned works and changes tracked with MOPs, approvals, evidence and rollback steps attached, so nothing happens in the hall without a record.
Colocation customer portals
Colocation and wholesale clients see their own power, cooling, tickets, SLA performance and billing, generated from the same governed data as your internal reporting.
Compliance & audit reporting
ISO 27001, SOC 2, Uptime tier commitments and client audit requests answered from retained evidence: alarms, changes, maintenance and access, versioned and attributable.
The digital twin
Test it in the model
before the hall.
A digital twin is a live model of your facility, fed by the sensor data you already have. Its purpose is practical: see how the hall really behaves, try changes safely, and rehearse failures before they happen. Model quality is only as good as the sensor data feeding it, so we start by checking what your instrumentation can actually tell you.
Live thermal & airflow picture
The twin mirrors hall conditions from the sensor feeds you already have: temperatures, pressures, airflow and power draw. Engineers see how the hall actually behaves, not how the design assumed it would.
What-if before you touch anything
Containment changes, setpoint schedules, fan speeds and new rack loads are tested in the model first. The predicted effect is reviewed before any change reaches real plant.
Failure rehearsal
Chiller failure, UPS transfer and A/B power loss scenarios rehearsed in the model, so runbooks are tested against evidence instead of memory.
Capacity planning
Where the next megawatt of IT load can actually land, based on measured cooling and power headroom rather than nameplate figures. Capacity decisions rest on the same data as operations.
Commissioning support
New halls and retrofits commissioned against the twin before IT load arrives, so gaps between design and reality are found early.
AI in the facility
AI around the plant,
never in charge of it.
AI can remove the work that surrounds a facility: triaging alarms, spotting drift, drafting schedules, preparing audit packs. The line we hold is clear. AI prepares, drafts and tests in the model. Setpoints, plant, transfers and safety stay with your engineers.
Anomaly detection
Sensors drifting, plant hunting and equipment running out of character are detected from trend data before they become incidents. Each finding links to the readings that produced it.
Cooling optimisation assistance
Setpoint and schedule suggestions built from load, weather and tariff signals, so the facility runs efficiently without anyone freezing. Every suggestion is reviewed before it applies.
Predictive maintenance
CRAC units, pumps, chillers and UPS batteries likely to fail are flagged with their run history, so maintenance is planned instead of reactive. The intervention decision stays with your engineers.
Power chain analysis
A/B feeds, transfer behaviour and single points of failure surfaced from live data, so resilience claims are checked against what the facility actually does.
Capacity forecasting
Demand growth projected against measured headroom, so expansion, pre-sales and energy contracts are planned on evidence.
Document & procedure search
MOPs, SOPs, O&M manuals and commissioning records searchable in plain language, so an engineer gets the answer in seconds during an incident.
One change, end to end
Detected, approved,
twin-tested, logged.
The scene below traces one change through the platform: a sensor drifts, AI drafts the action and an engineer approves it, the change is tested in the twin before it touches the hall, and the outcome is applied and logged.
Drift detectedTriage & approvalTwin-testedApplied & logged
Controls & accountability
Boundaries agreed
before the build.
Your operations, compliance and legal owners confirm the rules that bind your facility; we translate them into engineering controls and review evidence. This is not a compliance certification.
AI never takes direct control of plant
Setpoints, plant starts, transfers and safety systems stay with your engineers and your control logic. AI observes, drafts and suggests. People decide, always.
Safety systems stay independent
Fire, life safety and critical alarms remain on their certified systems. We read from them; we never sit in their path.
The twin is a model, not the building
Twin predictions are advisory. Any change to real plant goes through your change process with an engineer approving, and the twin's assumptions are documented so its limits are known.
Evidence travels with every action
Readings, alarms, suggestions, approvals and changes are retained against each asset and exportable, so an audit or client review is answered from records, not memory.
Logs you can audit
Every AI-assisted action is logged with the actor, the source it worked from and the outcome, so your team can verify exactly what the system did.
Deployment choices
Where it runs
is your call.
Some operators are comfortable with a compliant vendor cloud. Others need facility and client data to never leave their own boundary. We support both, and we will tell you honestly what each one costs in operations and flexibility.
Compliant cloud
A vetted provider configured under the appropriate data agreements, in your region, with data handling agreed in writing.
Private deployment
The platform runs in a private cloud or data centre you control: your region, your network, your keys.
Fully self-hosted
Open-weight models and the entire stack inside your own infrastructure. Facility data never crosses your boundary; you own the operation entirely.
How we work
A clear path from
discovery to launch.
- 01
Walk the hall
We start with how the facility actually runs: the plant, the sensor coverage, the alarm load and the workarounds your engineers rely on. The gaps become the design brief.
- 02
Agree controls & boundaries
What runs automatically, what waits for an engineer and where data may go are written down with your operations and compliance owners before production code exists.
- 03
Build with AI-assisted engineering
Engineers and coding agents build in parallel under the same discipline: access controls, audit logging and data boundaries are part of the build, reviewed at every step.
- 04
Prove it on live plant
We test the critical journeys with live sensors, real alarms and real load, produce the evidence your reviewers need, and support launch with a clear recovery plan.
Before we start.
What exactly is the digital twin?
A live model of your halls fed by the sensor data you already have: thermal and airflow behaviour, power chains and capacity. It is used to test changes, rehearse failures and plan capacity before anything touches real plant. It is not a 3D visualisation; the value is in the physics and the evidence.
Does the twin need perfect sensor data?
No. We scope the model to what your instrumentation can actually tell us, and where it matters we plan the sensors that close the gap. Model quality is only as good as the data feeding it, and we say so honestly.
Can AI adjust cooling or start plant by itself?
No. AI detects the issue, assembles the context and drafts the action. An engineer approves it. Direct control of plant without judgement is how facilities go wrong quietly.
Do you replace our BMS or DCIM?
No. We integrate with your existing systems and keep them as the system of record. The platform adds monitoring, analysis, workflows and reporting on top.
Can our data stay inside our own infrastructure?
Yes. We offer a compliant vendor cloud, a private deployment in your region, or fully self-hosted with open-weight models inside your own boundary. We will tell you honestly what each option costs in operations and flexibility.
How do you measure success?
We agree the measures during discovery: PUE and efficiency trends, incident rates, first-time fix, capacity utilisation and audit readiness. The reporting is built on the same governed data as the product.
How long does a first release take?
It depends on scope and integrations. After discovery we give you a scoped estimate for the smallest useful release, typically one hall or one system, and a plan for what follows.
Let's talk
Where does your capacity
and efficiency go missing?
Tell us about the halls you run, the systems you depend on and the clients you answer to. We will help you scope a first release that is reliable, well-controlled and provably well-built.