Platform Federator.ai Cortex Full-Stack Implementation Sovereign AI NVIDIA Alignment Leadership Contact
AI-Driven Data Centers
Revenue = Tokens per Watt x Available Gigawatts

AI-Driven Data Centers for the AI-Driven World

Turning data centers into adaptive AI factories—
flexible, autonomous, and future-proof.

94% GPU Failure Prediction Accuracy
IT+OT Unified Management Plane
GB300 NVL72 Ready Infrastructure
16+15 US Patents Granted + Pending
SOVEREIGN AI NEO-CLOUD
SOVEREIGN AI NEO-CLOUD
SOVEREIGN AI NEO-CLOUD
Americas
DGX GB200
DGX H100
Liquid Cooling Active
EMEA
DGX GB200
2.4 MW
APAC
DGX H100
HGX B200
ADDC.ai Orchestration
Healthcare
Finance
Research
Education
Autonomous
GenAI
2,547,392 GPUs Active
94.2% Utilization
12 Failures Predicted
Global View / Americas

Americas Data Center

Virginia, USA
Operational
1,024 Total GPUs
+12 this week
94.7% Utilization
18.4 MW Power Draw
PUE: 1.12
18°C Coolant Temp
Delta: 12°C
3.2 Tb/s Network I/O
$2.85 $/GPU-hr
-$0.12 vs avg

Active Workloads

Training 45%
Inference 35%
Fine-tuning 15%
Training Inference Fine-tuning Available

GPU Health & Predictions

892 Healthy
18 Predicted Issues
8 Scheduled Maintenance
6 Offline

Rack Layout (Click to drill down)

A-01
A-02
A-03
A-04
Cooling Aisle
B-01
B-02
B-03
B-04 Maintenance
Data Center / Rack A-01

Rack A-01

DGX GB200 NVL72 - 72 GPUs
Operational
Compute Tray 8 Online
B200
B200
B200
B200
B200
B200
B200
B200
Compute Tray 7 1 Predicted Failure
B200
B200
B200
72h
B200
B200
B200
B200
B200
Compute Tray 6 Online
B200
B200
B200
B200
B200
B200
B200
B200
+ 5 more compute trays
Liquid Cooling Distribution Unit Active
18°C Inlet
30°C Outlet
Flow Rate: 45 L/min Pressure: 2.1 bar
Power Distribution Active
285 kW
Capacity: 350 kW Efficiency: 98.2%

GPU Failure Prediction Analysis

GPU-63 (Tray 7, Slot 3) 94% confidence
72 hours until predicted failure

Anomaly Signals Detected

! Memory ECC Errors +340% above baseline
! Thermal Cycling Stress Pattern match: 87%
! Power Draw Variance +12% instability

Recommended Actions

Scheduled Migrate active workloads to GPU-64 (adjacent slot)
Pending Schedule replacement during next maintenance window

The $100B Infrastructure Dilemma

"I didn't want to get stuck with massive scale of one generation... The pacing matters, the fungibility and the location matters, the workload diversity matters."

Satya Nadella CEO, Microsoft

Root Causes of AI Training Interruptions

Source: Meta LLaMA 3 Training Study, 16,384-GPU cluster

GPU / HBM Hardware
50%
Network Issues
20%
Software Bugs
15%
Other
15%

ADDC.ai's Federator.ai Cortex directly addresses the #1 cause with 94% failure prediction accuracy

Uncertain ROI

$100B+ investments in GPU data centers with uncertain 5-7 year utility horizons

Rapid Evolution

Hardware generations evolve faster than infrastructure can adapt

Unpredictable Workloads

Training, inference, and emerging AI applications demand different resources

Dynamic Requirements

Cooling and power demands change dramatically with each GPU generation

+50pp GPU Utilization Gain
50% Fewer Training Failures
+45% Cooling Throughput
0s Maintenance Downtime
2x GPU Efficiency

Transform Static Infrastructure into Adaptive AI Factories

"The world's data centers... are now AI factories that produce a new commodity: artificial intelligence."

Jensen Huang CEO, NVIDIA

ADDC.ai transforms static data centers into Adaptive AI Factories—infrastructure that evolves with workloads, predicts failures before they happen, and optimizes resources in real-time.

Federator.ai Cortex

The Adaptive AI Ops Platform for AI Factories

AboveCloud Platform

The Global AI Compute Marketplace

AI Workloads
Federator.ai Cortex
IT + OT Infrastructure

The Intelligence Layer for AI Factories

Five core capabilities that transform GPU infrastructure operations

AI-Driven Operations (AIOps)

Real-time optimization engine for the AI Factory

Continuously analyzes and autonomously shapes cluster layout and job distribution. Includes Martin-SRE autonomous agent for self-healing operations and Wingman AI natural language copilot for fleet queries:

  • GPU utilization patterns
  • Interconnect congestion
  • Thermal profiles
  • Memory bandwidth pressure
  • Failure-prediction signals
  • Power/cooling limits
  • Martin-SRE autonomous remediation
  • Wingman AI natural language fleet queries

Adaptive Distributed Parallelism (ADP)

Beyond rigid DDP/ZeRO/Pipeline choices

Dynamically selects and reconfigures parallelism strategies. Integrated with KAI Scheduler for intelligent GPU-aware job scheduling based on:

  • Dataset size & model topology
  • Power & cooling constraints
  • Network saturation
  • GPU health state
  • KAI Scheduler GPU-aware job placement

Peak efficiency whether training 70B models or running agentic pipelines.

IT + OT Convergence

One control plane for full-stack awareness

Most AI failures today come from OT blind spots. ADDC.ai integrates:

  • IT telemetry: jobs, kernels, GPU metrics
  • OT telemetry: CDUs, cooling loops, power feeds, racks

Proof of Trust 4-phase autonomous governance:

  • Phase 1 - Shadow: AI observes, human controls
  • Phase 2 - Advisory: AI recommends, human approves
  • Phase 3 - Autonomy: AI acts, human monitors
  • Phase 4 - Full: AI operates autonomously

Full-stack situational awareness for the AI Factory.

Future-Proofed GPU Investments

The answer to "Will my investment still be useful in 3 years?"

The single biggest fear for GPU facility owners—ADDC.ai ensures the answer is yes:

  • Multi-generation GPU coexistence
  • Dynamic workload routing to match capabilities
  • Predictive cooling and derating for older GPUs
  • Heterogeneous cluster orchestration with maximal ROI
  • kMotion live migration for zero-downtime GPU maintenance

The NVIDIA Ecosystem Alignment

Jensen Huang declared that "every company will have an AI factory" and that data centers are becoming factories that manufacture intelligence.

Traditional Data Center AI Factory with ADDC.ai
Static capacity planning Dynamic workload adaptation
Reactive maintenance Predictive GPU failure prevention
Siloed IT/OT management Unified operational intelligence
Fixed hardware generations Generation-agnostic operations
Local optimization Global compute federation

Built for Tomorrow's AI Infrastructure

JH
Jensen Huang CEO, NVIDIA

"The world's data centers have become AI factories. They take in raw data and produce intelligence."

ADDC.ai Response:

AI Factories require AI Operations. You cannot manufacture intelligence at scale with manual operations and siloed systems.

JH
Jensen Huang CEO, NVIDIA

"Accelerated computing and generative AI have reached the tipping point."

ADDC.ai Response:

ADDC.ai ensures your AI Factory infrastructure keeps pace with exponential AI growth—adapting to new GPUs, workloads, and efficiency requirements.

SN
Satya Nadella CEO, Microsoft

"The key thing for us is to have our builds and leases be positioned for what the workload growth of the future."

ADDC.ai Response:

Our platform enables infrastructure that evolves with workloads rather than constraining them. No more betting on obsolete assumptions.

SN
Satya Nadella CEO, Microsoft

"Building infrastructure that can serve any workload, anywhere."

ADDC.ai Response:

The AboveCloud Platform creates a global fabric where compute resources flow to workloads based on real-time demand, location, and efficiency metrics.

Federator.ai Cortex — AI Ops for AI Factory

The Adaptive AI Ops Platform for AI Factories — bridging IT intelligence with OT operations. Protected by 16 US Patents + 15 Pending.

AI Workloads & Applications
LLM Training
Real-time Inference
Fine-tuning
Agentic AI

Federator.ai Cortex

The Adaptive AI Ops Platform for AI Factories
AI Ops Engine Real-time optimization
ADP + KAI Scheduler Adaptive Parallelism
IT/OT Bridge Unified management plane
Martin-SRE Autonomous agent
kMotion Live GPU migration
IT Telemetry
OT Telemetry
IT Infrastructure
DGX GB300 NVL72 72 GPUs / Rack
DGX H100 8 GPUs / Node
NVLink / InfiniBand High-speed interconnect
OT Infrastructure
Liquid Cooling CDU 200-300 kW / Rack
Power Distribution PDU / UPS / Switchgear
Facility BMS HVAC / Fire / Security
AboveCloud Platform

Global AI Compute Marketplace - Federate capacity across sites, optimize workload placement, enable compute trading

GB300 NVL72 Ready Native support for NVIDIA's latest 120kW liquid-cooled racks with full thermal management integration
Full-Stack Visibility From CUDA kernels to coolant temperatures - one unified operational view
Multi-Generation Support Manage H100, B200, and GB300 clusters from a single control plane
NCP 19/19 APIs
NVIDIA Certification Program
SOC2 Ready
HIPAA Compliant
16 US Patents
Kubernetes Native

Full-Stack AI Factory Implementation

Reduce deployment from 18 months to 3 months. Maximize ROI from Day 1.

$100M+ Cost per day of downtime for a 1GW AI Factory
<30% Typical GPU utilization without proper orchestration
40-60% Faster deployment with modular prefabricated solutions

Modular Construction Integration

Pre-integrated with prefabricated modular data center designs. Factory-tested rack-level configurations arrive ready to deploy, reducing on-site construction time by 40%+ and eliminating integration surprises.

  • Rack-level pre-configuration
  • Factory validation & testing
  • Parallel site preparation

Ready-to-Serve Power

Optimized for high-density 120kW+ racks from day one. Intelligent power distribution that scales from first rack to full capacity, with real-time PUE optimization under 1.15.

  • 120kW per rack support
  • Intelligent load balancing
  • PUE optimization <1.15

Rack-Level Orchestration

GPU servers managed at rack granularity with NVIDIA DGX GB200 NVL72 native support. 72 GPUs per rack operate as unified compute with 2L/s liquid cooling at 25°C inlet.

  • 72 GPU unified management
  • NVLink topology awareness
  • Liquid cooling integration

Deployment Timeline Comparison

Traditional Build
Planning
Construction
Integration
Test
18-24 months
With ADDC.ai + Modular
Plan
Parallel Build
Deploy
Optimize
3-6 months

Prefabricated modules are built and tested in parallel with site preparation. Federator.ai Cortex is pre-installed and validated before shipping.

Sovereign AI Ready

Accelerating national AI initiatives with packaged, ready-to-deploy AI Factory solutions

Nations worldwide are investing over $50 billion in sovereign AI infrastructure. The challenge isn't just building data centers—it's operating them effectively while maintaining data sovereignty and enabling local innovation.

Packaged AI Applications

Pre-validated AI application stacks for critical national services, reducing time-to-value from years to months.

Healthcare AI Education Citizen Services Agriculture Financial Services Emergency Response

Local Language LLMs

Infrastructure optimized for training and deploying language models in local languages, preserving cultural context and data sovereignty.

20+ Ready-to-use AI apps
100% Data residency

Turnkey Deployment

Complete AI Factory solution including infrastructure, software, and operational support—from site selection to production workloads in months, not years.

  • Site assessment & planning
  • Modular facility deployment
  • GPU rack installation
  • Software stack configuration
  • Operational training

Supporting Sovereign AI Initiatives Worldwide

🇪🇺 EuroHPC
🇮🇳 IndiaAI Mission
🇦🇪 UAE AI Strategy
🇯🇵 Japan AI
🇸🇬 Singapore
🇲🇾 Malaysia
🇮🇩 Indonesia
🇨🇦 Canada

Technology Differentiators

01

Cross-Layer Causal Analysis

Patented Multi-Layer Correlation engine (US Patent 11,579,933) discovers causal relationships across GPU workloads, network fabric, cooling systems, and power distribution in real time. When performance degrades, Cortex traces root cause across application, infrastructure, and environmental layers simultaneously—not just monitoring, but understanding why things fail and what to do about it. No single-layer tool can see what Cortex sees.

02

Spatial & Temporal GPU Optimization

World's first patent for spatial and temporal GPU optimization. Predictive 4D scheduling engine optimizes workload placement across time, space, power, and thermal dimensions. Integrates with NeMo Megatron, DeepSpeed ZeRO, Ray, and Alpa for adaptive parallelism selection that maximizes training throughput across heterogeneous GPU generations (H100, B200, GB300, and future architectures).

03

Autonomous AI Ops Agents

Martin-SRE autonomous agent detects, diagnoses, and remediates GPU failures without human intervention—replacing brittle runbooks with AI agents that reason, adapt, and act. Wingman AI delivers natural language copilot access for fleet-wide queries and incident investigation. LangGraph-powered multi-agent pipeline coordinates triage, cooling, billing, and maintenance autonomously. Reduces operational headcount by 60–80%.

04

Smart Liquid Cooling 2.0

Model Predictive Control (MPC) thermal management for 200kW+ rack densities. Adaptive coolant flow optimization with rack-level heatmap monitoring that responds to workload intensity in real time. HVAC integration for holistic facility thermal management. Achieves 45% higher cooling throughput than manual BMS while maintaining GPU junction temperatures within optimal operating range.

05

8-Mode GPU Failure Prediction

ML-driven anomaly detection pipeline across 8 failure modes with 72-hour advance warning at 94% accuracy. Health dimension radar monitors ECC errors, thermal cycling stress, power draw variance, and more. Graceful workload migration via kMotion live migration before hardware degradation impacts training or inference SLAs. Critical for 200–300kW racks where a single failure can wipe out multimillion-dollar training runs.

06

Proof of Trust Governance

Autonomous operations require earned trust, not blind trust. Cortex deploys AI agents through four progressive governance phases—Shadow, Advisory, Autonomy, and Full—each with cryptographically hashed evidence packs and tamper-proof audit trails. This framework ensures safe, verifiable autonomy progression while maintaining complete operational accountability and compliance readiness.

Optimized for Every Frontier

Purpose-built configurations for the most demanding AI workloads across industries.

Financial AI

Ultra-low-latency inference for real-time trading models, risk analytics, and regulatory compliance pipelines.

SOC2PCI-DSSSub-5ms

Biotech & Pharma

Accelerated molecular simulation, protein folding, and genomic sequencing with sovereign data residency.

HIPAAFDA-AlignedGxP

Enterprise LLM

Fine-tuning and serving at scale for proprietary large language models with enterprise-grade security.

SOC2SovereignMulti-Tenant

AI SaaS Platforms

Elastic GPU infrastructure for SaaS platforms shipping AI features to millions of end users.

SOC2Auto-Scale99.99% SLA

Transform Your Data Center Into an Adaptive AI Factory

Whether you operate 2 MW or 200 MW, Federator.ai Cortex is the AI Ops platform purpose-built for AI-Driven Data Centers.

Revenue = Tokens per Watt x Available Gigawatts
Higher GPU cluster ROI
Longer hardware lifespans
Safer liquid cooling at extreme density
Predictable operations
Lower operational costs
Infrastructure that won't go obsolete

For NVIDIA: NVIDIA has built the world's best compute platform. ADDC.ai is the intelligence layer that ensures every GPU in the facility operates at its highest possible economic and technical value—maximizing token output per watt, the defining metric of AI Factory profitability.