Physical AI Platform

Where Digital Intelligence Meets Physical Reality

Next-generation AI products that transform critical infrastructure across water, telecommunications, healthcare, energy and government.

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This video, generated by AI, uses fictitious people and scenarios to illustrate the powerful insights and outcomes our products can help leaders achieve.

The Physical AI Advantage

Real-world systems generate data from sensors spread across complex infrastructure. Successful AI applications must adapt with this physical information to deliver accurate insights and actionable intelligence. Our Physical AI framework achieves this in all three phases of data intelligence:

Sense

Collect data from ruggedized physical infrastructure

Analyze

Process information using AI models trained on real-world conditions

Act

Enable automated responses and improved human decision-making

Our product architecture

Our core product is “Sand OS” – an enterprise-grade data platform that helps organizations aggregate, analyze, and act upon complex data.

AI Co-Pilot
Co-Pilot
Data Visualization
Visualization
Data Platform
Platform
Infrastructure Layer
Layers

AI Co-Pilot

The AI Co-Pilot layer acts as a force multiplier, allowing users to engage with the model, perform automations and make faster, more-informed decisions based on real-world data.

Data Visualization

Effective data visualization translates vast, complex datasets into understandable graphical insights, allowing people to identify patterns, detect biases and interpret the model's results.

Data platform

The robust data platform provides a backbone for AI models, enabling clean, organized and accessible data for unmatched training, enrichment and real-world performance.

Infrastructure Layer

Our enterprise-grade data platform enables organizations to aggregate, analyze and act on complex data. The infrastructure layer provides the foundation for our Source, Ingest, Enrich, Serve, Engage (SIESE) framework.

Built for Speed and Scale

Our secure, real-time, digital-twin platform provides an engine for scaled AI deployment. It unifies fragmented data and bridges the physical-digital gap, enabling a progression from situational awareness to forecasting, simulation and system-wide optimization.

Unified Data Layer

Consolidates fragmented data sources into a single, real-time digital twin

Modular Architecture

SIESE framework enables reusable components across domains

Develop Tools

Platform Workbench for engineers to onboard and configure Co-Pilots

Progression of Capabilities

1
Situational Awareness

Understand what is happening

2
Forecasting

Predict what will happen

3
Simulation

Test actions prior to implementation to identify outcomes

4
Optimization

Integrate prescriptive actions to maximize results

Four-Step AI Journey

  • Make infrastructure intelligent by connecting it to sensors, cameras and other hardware
  • Aggregate data that data scientists then use to create digital twins of the physical world based on industry specialization
  • Visualize the data to always understand the status of operations and assets
  • Leverage AI Co-Pilots to make more-informed CapEx and OpEx decisions

Powerful Results

Utilities

$100M+ Savings from regulatory fine
50% Reduction in leakage

Telecommunications

95% population-weighted coverage across the country.
$200M in savings vs other proposed rollouts.

Health

125+ Health posts digitized with EMRs, Starlink & solar
1,121,047 Patients served

Utilities

$ 0 M+
Savings from regulatory fines

Utilities

0 %
Reduction in
leakage

Telecommunications

0 %
population-weighted coverage
across the country.

Telecommunications

$ 0 M
in savings vs other
proposed rollouts.

Health

0 +
Health posts digitized with
EMRs, Starlink & solar

Health

0 M+
Patients 
served

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