HyperStream™ – Intelligent Data Pipelines for AI
Streaming data the way AI thinks — real-time, contextual, and always ready.
AI doesn’t wait. Neither should your data. HyperStream delivers a unified, intelligent pipeline architecture to move data across edge, cloud, and GPU-native systems with maximum performance and zero-touch orchestration.
The Problem with AI Data Pipelines.
🧊 Latency Bottlenecks — Data doesn’t arrive fast enough for real-time inference
🧱 Brittle ETL Workflows — Batch jobs and static schedules slow down AI agility
🗂️ Storage Mismatch — Legacy storage systems aren’t built for GPU bursts
🌐 Edge Disconnection — Data from the edge often arrives late or not at all
🧑🔧 Manual Orchestration — Engineers manage pipelines instead of optimizing models
AI-native systems don’t just need more data. They need smarter, faster, intent-aware data pipelines.
The HyperStream™ Architecture
Fast. Adaptive. AI-Aware.
StreamIQ
Real-time streaming engine with intent-aware data DAGs and orchestration rules
PulseCache
Memory-optimized caching and tiered storage fabric for latency-sensitive pipelines
EdgeFlow
Lightweight edge-native runtime for local inference and smart preprocessing
InferSync
Ultra-low-latency pipeline for inference delivery and real-time model data syncing
DataMeshIO
Adaptive routing and transport fabric with AI-aware flow control
AIDataOS
Unified control and policy layer for managing distributed AI data pipelines
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Data Acceleration & Storage Optimization
⚡ Use tiering, memory-mapped caching, and adaptive prefetching to reduce I/O bottlenecks.
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Edge AI & Decentralized Processing
🌍 Push inference and preprocessing closer to the data source — at the edge.
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AI-Driven Orchestration
🧠 Let AI determine what data moves, when, and how — tuned for freshness, context, and workload intent.