Optimize Deep Learning
Models for Cost-effective
Cloud Inference at Scale

Deci’s platform optimizes your deep learning models, to maximize the utilization of any cloud compute instance, enabling compute-flexibility and cost-efficient cloud inference without compromising accuracy.

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The Challenge

Operating your deep learning models in cloud environments is a costly matter and high inference costs can dramatically cut down your product’s profitability. Companies want to offer end-users a high-performance deep learning model, without compromising on the model’s accuracy and SLA. However, customers are also challenged with finding the appropriate cloud-based compute configuration required for their scalable model inference tasks. For example, in today’s general-purpose cloud environments, customers may need to choose and trade-off between using a lower-cost cluster of CPU-based compute instances and a higher-cost, top-performing single dedicated GPU-based compute instance. At the end of the day, companies face the dilemma of executing model inference models at a lower operating margin but with high performance or sacrificing the user experience with poorly-performing deep learning models.

Deci’s Deep Learning Platform

Connecting your model to the platform and using the AutoNAC technology will enable a cost-effective deep-learning model workload that is performance-optimized for any selected target cloud compute instance. You can save cloud operating costs by maximizing the utilization of your existing cloud environment or even consider switching to cheaper instances, while preserving the same model accuracy and SLA.

Benefits:

  • Cut your cloud compute bill by maximizing the throughput of your deep learning models
  • Reduce costs by running on less expensive cloud compute instances
  • Scale up your solution on existing hardware without extra cost

All without compromising on performance or accuracy!

Achieve State-of-the-Art Performance, Powered by AutoNAC™

Boost your trained model’s throughput/latency for any hardware, with Deci’s AutoNAC algorithmic optimization, without compromising on accuracy.

GPU
  • Nvidia T4
  • ResNet-50
  • ImageNet
CPU
  • Intel Xeon Gold 6328H 8-core
  • ResNet-50
  • ImageNet

Applications

  • Video Analytics
  • Security Cameras
  • Medical AI Diagnoses
  • Manufacturing
  • Image Editing
  • Your Application >

Deployment Options

Cloud Deci

Cloud

  • AWS, GCP, Azure
  • CPU and GPU
Cloud Deci

Cloud

  • AWS, GCP, Azure
  • CPU and GPU
wsc sports improve AI models using Deci AI

"We are excited to be working with Deci's platform - it provided amazing results and achieved 4.6x acceleration on a model we ran in production and helped us provide faster service to our customers.”

Daniel Shichman, CEO, WSC Sports Technologies

Relevant Resources

Blog

Deci RTiC – The Case for Containerization of AI Inference

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WSC Sports Video Platform Reduces Cloud Cost by 78%

Case Study

WSC Sports Video Platform Reduces Cloud Cost by 78%

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Press Release

Deci Named One of CB Insights' 100 Most Innovative Startups

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Maximize the Potential of Deep Learning