Data Center
AI has rewritten the rules of data center design. Rising compute density, increasing energy demands, and evolving infrastructure requirements call for a new engineering approach.
At LTTS, we engineer the complete AI data stack – from energy and infrastructure to compute and intelligence – so that power, cooling, silicon, and software work together as one integrated system.
The future of AI-ready infrastructure starts here, and LTTS is engineering it from the grid to the chip.
LTTS datacentertjänster – Från chip till elnätet!
AI has Outgrown the Traditional Data Center
A single AI query can draw roughly ten times the power of a web search, and workloads are only becoming more demanding. Global data center electricity demand is expected to more than double, from 415 TWh in 2024 to about 945 TWh by 2030 (IEA). Infrastructure designed for predictable, moderate-density workloads cannot simply be scaled up to meet the demands of AI.
Four forces are compounding at once, and they can no longer be solved one silo at a time:
Power as the bottleneck
Where traditional facilities drew 10–25 MW, hyperscale AI centers can exceed 100 MW (IEA). Energy availability, distribution and resilience now shape data center design rather than supporting it as an afterthought.
Cooling is mission-critical
Nearly half a data center's energy is used for cooling. As rack densities increase, direct-to-chip and immersion cooling essential, not optional.
Compute moves to rack-scale
Performance is now engineered at the rack level - across silicon, servers, networking, storage, and firmware: not bought as a box and simply deployed.
Operations become autonomous
At this scale and complexity, reactive, manual, multi-vendor operations are no longer sustainable. Data centers must observe, predict, and respond autonomously.
Engineering the AI Data Center as One Intelligent system
As an integrated engineering partner, LTTS brings together four critical layers – Energy, Infrastructure, Compute, and Intelligence – into one unified engineering approach. This is what Engineering Intelligence means for AI data center: designing the physical infrastructure and the software that powers it as one connected system.
Energy
Engineer resilient, efficient power system - from the grid and switchgear to backup power and the rack, ensuring reliable energy for high-density AI workloads.
Infrastructure
Design intelligent cooling and facility infrastructure that supports high-density AI workloads through advanced air and liquid cooling, HVAC, building management, and security systems.
Compute
Optimize AI performance through GPU-first racks, boards, power, firmware, and silicon engineering —delivering compute designed for next-generation AI workloads.
Intelligence
Enable autonomous operation with AI-driven observability, digital twins, and DataMind, our AI -native DCIM platform that predict failures before they become outages.
Engineering Capabilities Across Every Layer
Engineered as one chain, not four handoffs.
Grid → Power → Cooling → Compute → Intelligence
Powering resilient AI infrastructure
- Power generation & transmission
- MV/LV switchgear
- Static transfer switching
- UPS & backup power
- Battery energy storage (BESS)
- Renewable & microgrid integration
- Digital substations
- Power distribution optimization
Optimized for high-density AI
- Air & liquid cooling
- CFD thermal modeling
- HVAC
- Building management & automation
- SCADA/BMS integration
- Fire safety
- Physical & cyber security
- Sustainability & decarbonization engineering
Engineered for AI performance
- Custom GPU-first rack & server design
- High-speed board design
- BMC/IPMI/Redfish firmware
- Multi-million-gate silicon & chipset engineering
- Pre- and post-silicon validation
- Full-rack integration & certification
Autonomous operations at scale
- AI-native DCIM Platform
- AIOps & observability
- Digital twins
- Predictive maintenance
- Energy & workload optimization
- 24×7 managed operations
- Cybersecurity operations
- IT/OT integration
DataMind
DataMind is LTTS’ AI-native DCIM platform that unifies multi-vendor data center operation through open protocols. Its five AI agents work together to predict failures 48–72 hours in advance, enabling proactive, autonomous operations, not just dashboards.
LTTS datacentertjänster – Från chip till elnät!
Built for the Companies Building AI Infrastructure
From hyperscalers to enterprises, we engineer AI infrastructure at every stage of the journey.
Hyperscalers & colocation
Design and operate greenfield AI factories, high-density retrofits, and AI-driven managed operations across multi-vendor environments
Data center OEMs / ODMs
Accelerate product innovation with custom rack and server design, board and firmware engineering, silicon validation, and lifecycle sustenance
Enterprises
Modernize enterprise data centers and deploy, private AI infrastructure across BFSI, telecom, manufacturing, energy, and the public sector
And Beyond: We Support the broader AI ecosystem; from power and energy developers to semiconductor, networking and system integration partners.
Where We Engineer
Whether you are building, modernizing, or operating AI infrastructure, LTTS delivers full-stack engineering across the entire data center lifecycle.
What we do
Engineer integrated power, cooling, rack and controls system for greenfield, and high-density AI facilities.
Outcome
Grid-to-Chip engineering
What we do
Deliver 24×7 Engineering Intelligence-led operations with AI observability and predictive maintenance across multi-vendor environments.
Outcome
99.9% availability
What we do
Retrofit power and cooling for AI workloads with CFD-based thermal redesign and phased, low-disruption migration.
Outcome
AI-ready, minimal disruption
What we do
Deploy DataMind's five-agent AI mesh to detect anomalies, predict failures 48–72 hours in advance, and automate corrective actions.
Outcome
Predict, and not react
What we do
Optimize thermal performance, integrate BESS and renewable microgrid, and carbon tracking.
Outcome
Lower PUE and OpEx
What we do
Engineer GPU-first racks and server, board and firmware solutions, and pre- and post-silicon validation for next-generation AI processors.
Outcome
Grid to Chip expertise