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Visit us at SCI ’25 | Dec 10–12, 2025 | Stall B77 | Manipal Institute of Technology (MIT), Bengaluru, India
Trndx Cloud Solution
Designed for Efficiency. Engineered for Scale.
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Our Solution - Topology Engineering
Infrastructure-in-Motion™
Dynamically Reconfigurable Multi-Topology Adaptive Infrastructure
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ACCELERATED. ADAPATIVE. AT SCALE.
Next-Gen Cloud Architecture
TrndX Breakthrough
Model Training
Ultra-fast, low-latency interconnect links
Reliable Data Pipelines
High-throughput, congestion-free
Rapid Experimentation
Fast spin-up of new clusters
Cost Efficiency Per GPU
Cuts idle time, network bottlenecks
Isolation
Strict workload separation and data security.
Solving Critical Infra Challenges
Infrastructure is in Crisis
Data surge
Data is the fuel- Creating unprecedented demand and bottlenecks.
Workloads are evolving
AI/ML workloads are rapidly outgrowing traditional cloud infrastructure demand.
Expensive, Inefficient
Existing infrastructure is expensive, power-intensive, and overly centralized, resulting in suboptimal utilization.
Traditional Architectures Fall Short. Static. Fixed
Hardwired Connections
Traditional connections are hard wired using links such as NVlink, Infiniband or ethernet fabrics.
Static Topologies
Topology is predefined- hard to change or rewire, once installed.
Frequent Hardware Refresh
Hardware elements are changing too frequently, outdating investments and their ROI window, there by undermining long-term value.
Infrastructure is in Crisis
-
Data surge
Data is the fuel- Creating unprecedented demand and bottlenecks.
-
Workloads are evolving
AI/ML workloads are rapidly outgrowing traditional cloud infrastructure demand
-
Expensive, Inefficient
Existing infrastructure is expensive, power-intensive, and overly centralized, resulting in suboptimal utilization. Frequent hardware refresh cycles are shrinking the ROI window and undermining long-term value.
Traditional Architectures Fall Short. Static. Fixed
-
Traditional connections are hard wired using links such as NVlink, Infiniband or ethernet fabrics.
-
Topology is predefined- hard to change or rewire, once installed
-
Hardware elements are changing too frequently, outdating investments and their ROI
Breakthrough is Needed.
Infrastructure is the Engine
Evolving and diverse nature of AI computations need to be accomofated for better perfomance.
Infrastructure must Adapt
Workload OptimizedReliable Data Pipelines - High-throughput, congestion-free Rapid Experimentation - Fast spin-up of new clusters.
Need for a Breakthrough
Infrastructure is the Engine.
Evolving and diverse nature of AI computations need to be accomodated for better perfomance.
Infrastructure must Adapt
Legacy data center designs face difficulties in scaling horizontally.
Breakthrough is Needed.
Infrastructure is the Engine.
Evolving and diverse nature of AI computations need to be accomofated for better perfomance
Scalability
Legacy data center designs face difficulties in scaling horizontally
Model Training - Ultra-fast, low-latency interconnect links
Isolation
Strict workload separation and data security.
Cost Efficiency Per GPU
Cuts idle time, network bottlenecks
Infrastructure must Adapt
Workload Optimized
Reliable Data Pipelines - High-throughput, congestion-free
Rapid Experimentation - Fast spin-up of new clusters
Infrastructure is in Crisis
-
Data surge
Data is the fuel- Creating unprecedented demand and bottlenecks.
-
Workloads are evolving
AI/ML workloads are rapidly outgrowing traditional cloud infrastructure demand
-
Expensive, Inefficient
Existing infrastructure is expensive, power-intensive, and overly centralized, resulting in suboptimal utilization. Frequent hardware refresh cycles are shrinking the ROI window and undermining long-term value.
Traditional Architectures Fall Short. Static. Fixed
-
Traditional connections are hard wired using links such as NVlink, Infiniband or ethernet fabrics.
-
Topology is predefined- hard to change or rewire, once installed
-
Hardware elements are changing too frequently, outdating investments and their ROI