Enterprise-ready ML infrastructure

Deploy machine learning in your own cloud

Pre-configured AMIs, containers, and SageMaker models that run inside your AWS account. Full control, no data egress, production-ready in minutes.

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  • Runs in your AWS account
  • No data leaves your VPC
  • Billed through AWS Marketplace

What we offer

AMIs, speech servers, and text models — all published on AWS Marketplace and deployed into infrastructure you own.

Need launch help for an AMI? AMI setup guide.

Browse the full catalog

Two ways to deploy

Choose the delivery model that fits how your team already works.

EC2 AMIs & containers

Ready-to-launch machine images and container images for AI workloads — deep learning notebooks, speech-to-text, text-to-speech. Launch into your own VPC and you own the instance.

  • Pre-configured ML environments
  • GPU and CPU optimized
  • Configurable at launch

SageMaker model packages

Production NLP models deployed to Amazon SageMaker in a couple of clicks. Sentiment analysis, named entity recognition, and more.

  • Real-time endpoints
  • Batch transform
  • JSON and CSV I/O

Why teams choose Sigmodata

Built for teams that need control, security, and speed.

Your data stays private

Everything runs in your own AWS account. Your data never leaves your VPC and never touches our servers.

One-click deployment

Subscribe and launch directly from AWS Marketplace. No procurement cycle, no DevOps project.

Tuned for the hardware

CPU builds that stay cheap on standard instance types, and GPU builds with CUDA and cuDNN already configured.

Production ready

Configurable through user data, documented APIs, and versioned releases you can pin to.

Ready to get started?

Launch your first environment in minutes, or talk to us about a private offer and custom models.

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