Your AI Command Central

On-premise computing platform that transforms raw data into intelligent automation. Load AI models, connect your systems, and orchestrate operations across any industry.

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One Platform, Infinite Applications

R2Box is where AI models come to life. Load vision models for autonomous surveillance, deploy fraud detection algorithms for financial security, or orchestrate multi-robot task management—all running on-premise with complete data sovereignty. The platform delivers 80-128 TOPS of edge computing power, providing the processing backbone for AI-driven operations without cloud dependency or latency concerns.

Whether you’re securing facilities, optimising workflows, or detecting anomalies in real-time, R2Box transforms specialised AI models into production-ready systems that integrate directly with your existing infrastructure.

See What’s Possible with R2Box

Intelligent Surveillance & Security

The Challenge:

Security teams monitor dozens of CCTV feeds manually, having to detect threats in real-time across multiple locations while reviewing hours of footage after incidents occur.

R2Box Solution:

Load vision AI models onto R2Box and connect your existing CCTV infrastructure. The system analyses footages in real-time, detecting intrusions, identifying unusual behavior patterns, recognising faces or license plates, and alerting security teams to threats before they escalate.

What This Enables:

  • Proactive Security: Real-time threat detection across all camera feeds simultaneously
  • Intelligent Alerts: Only notifies teams when actual threats are detected, reducing false alarms
  • Forensic Analysis: Rapid search through archived footage using natural language queries (“Show me all red vehicles entering Building A yesterday”)
  • Perimeter Monitoring: Automated detection of unauthorised access attempts or loitering

Industries: Corporate campuses, manufacturing facilities, logistics centers, retail chains, critical infrastructure

Multi-Robot Task Orchestration

The Challenge:

Operating multiple autonomous robots means managing complex task queues, battery states, and workload distribution. Manual coordination creates inefficiencies and downtime.

R2Box Solution:

Deploy work management AI models that intelligently orchestrate task distribution across robot fleets. When one robot runs low on battery, the system automatically rebalances the task queue, reassigning pending jobs to available units. The platform monitors robot health, predicts maintenance needs, and optimises routes to maximise fleet productivity.

What This Enables:

  • Dynamic Load Balancing: Tasks automatically reassigned based on robot availability and battery status
  • Zero Downtime: Continuous operations even when individual robots charge or undergo maintenance
  • Predictive Scheduling: AI anticipates task completion times and pre-positions robots for next assignments
  • Fleet Optimisation: System learns optimal task distribution patterns over time, improving efficiency

Industries: Warehouses, hospitals, manufacturing floors, hospitality operations, logistics hubs

Industrial Equipment Monitoring

The Challenge:

Manufacturing facilities face unexpected equipment failures that halt production lines, costing thousands per hour in downtime. Traditional scheduled maintenance may be too late.

R2Box Solution:

Deploy predictive maintenance models that analyse sensor data from industrial equipment (vibration, temperature, pressure, acoustic signatures) to predict failures before they occur. The system identifies early warning signs of bearing wear, motor degradation, or hydraulic issues—scheduling maintenance only when actually needed.

What This Enables:

  • Failure Prevention: Predict equipment failures 2-4 weeks in advance with 85%+ accuracy
  • Optimised Maintenance: Service only when needed, reducing maintenance costs by 20-30%
  • Production Continuity: Schedule repairs during planned downtime, avoiding emergency shutdowns
  • Asset Longevity: Extend equipment lifespan through proactive intervention

Industries: Manufacturing, oil & gas, utilities, transportation, food processing

Built for On-Premise AI at Scale

High-Performance Edge Computing

R2Box delivers 80-128 TOPS of INT8 inference capability powered by advanced AI accelerators, providing the computational backbone for running multiple AI models simultaneously. The platform features 12-24GB LPDDR5 memory, 64GB UFS 3.1 storage with NVMe expansion, and efficient thermal management that maintains performance under continuous operation.

Industrial-Grade Connectivity

Pre-built connectivity eliminates integration complexity. The platform includes 4-channel CAN-FD for industrial equipment communication, 3-channel RS-485 for legacy system integration, dual Gigabit Ethernet for network redundancy, WiFi 6 and 5G module support for wireless operations, and up to 8-10 camera inputs (MIPI CSI + GMSL) for vision applications.

Data Sovereignty & Security

All AI processing happens on-premise—your data never leaves your facility. R2Box satisfies data residency requirements, regulatory compliance mandates, and corporate security policies while delivering real-time inference without cloud latency. Built-in encryption, role-based access control, and audit logging ensure enterprise-grade security.

Flexible Deployment

Operating temperature range from 0°C to +60°C supports deployment in harsh industrial environments. Power input accepts 9V-48V DC with intelligent thermal management (passive + active PWM fan). Compact form factor fits into existing infrastructure without extensive facility modifications.

Technical Overview

AI Computing Power:

  • 80 TOPS (Standard) / 128 TOPS (Pro)
  • INT8, INT16, FP16 precision support
  • 160+ standard ONNX operators

Processing:

  • 6-core ARM Cortex-A78 CPU @ 1.5-2.0 GHz
  • ARM Mali G78AE GPU @ 100 GFLOPS
  • 4-core ARM Cortex-R52+ MCU for real-time control

Memory & Storage:

  • 12GB / 24GB LPDDR5 system memory
  • 64GB UFS 3.1 internal storage
  • M.2 NVMe expansion (up to 2TB)
  • microSD 3.0 support (up to 512GB)

Connectivity:

  • 4-channel CAN-FD
  • 3-channel RS-485
  • Dual Gigabit Ethernet
  • WiFi 6, 5G module support
  • 8-10 camera inputs (MIPI CSI + GMSL)

Operating System:

  • Ubuntu 22.04 LTS
  • Linux 6.1.112-rt43 Real-time Kernel
  • Framework support: TensorFlow, PyTorch, ONNX, Caffe

Power & Environment:

  • Power Input: 9V-48V DC (16V-48V default)
  • Typical Power: ~15W (Standard) / ~25W (Pro)
  • Operating Temp: 0°C to +60°C
  • Cooling: Passive + Active PWM fan

Ready to Transform Operations with On-Premise AI?

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