SwiftStack for distributed, at scale
AI & ML data pipelines

Leverage your most valuable asset - your data:
monetize new business models, glean predictive insights and enable competitive differentiation

Predictive to Prescriptive to Cognitive Analytics

Monetize your data at petabyte scale, with in-place Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) enabled by SwiftStack

AI/ML/DL storage workflow phases and their I/O challenges

AI/ML Workflow Phases

Why SwiftStack for AI/ML/DL data pipelines?

Cloud Native Architecture ✓

SwiftStack’s cloud-native architecture is a transformative storage platform for AI, ML and DL workflows. Traditional storage architectures are not designed for these new distributed workloads and fall short of performance, scale and value.


  • Enables hundreds of GB/s high ingest with massive concurrency and throughput to match the GPU compute layer parallelism

  • Provides broad application and protocol support for enterprise applications ingest with POSIX compliant filesystem (over NFS or SMB) as well as cloud native applications (AWS S3 or Swift APIs)


  • Supports rich metadata tagging, for contextualizing, supervised learning and other workflows

  • Metadata search integration to isolate data sets

  • Leverage SwiftStack 1space for lifecycle management with metadata tagging


  • In-place neural net training, with native S3 support for TensorFlow frameworks

  • Massive read bandwidth

  • Architectural separation of compute and storage enables massive scalability of training datasets

  • SwiftStack 1space enables cloud-bursting for best and cost efficient on-premises or across cloud GPU compute farms


  • Enables Inferencing at the edge or core


  • Policy based lifecycle management with metadata tagging, cloud tier, governance, massive scale with best economics

Use Cases

AI/ML/DL solutions are currently used across several vertical use cases:

Autonomous Vehicles

Autonomous Vehicles
  • Assisted Driving / ADAS
  • Telematics
  • Predictive Maintenance


  • Cancer anomaly detection
  • Pharma
  • Medical imaging
  • Pharma drug research


  • Predictive maintenance
  • Process optimization
  • Demand forecasting

Media and Entertainment

Media and Entertainment
  • Targeted Marketing
  • Content classification


  • Customer Churn
  • Cataloging
  • Supply Chain Management

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