90% of AI initiatives fail to produce ROI. We solve that.

Deploy, scale, monitor, and optimize production ML from the cloud to the edge quickly, efficiently, and using minimal engineering with our ML ops production platform.

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The fastest way to scale AI to ROI, right from the comfort of your own data science home

Deploy + Serve

Start inferencing at scale in seconds with the Wallaroo platform, using the infrastructure you’re already familiar with

Observe + Optimize

Monitor, test, and manage your production ML in Wallaroo’s unified operations center, shortening feedback loops and gaining agility

Expert ML Team

Get dedicated experts who’ve already been there and done that to support you as needed, from deployment to scaling to optimization

How it works

The Wallaroo Enterprise Platform for ML in Production. Your Tools, Your Data, Your Ecosystem.

Wallaroo.AI provides a simple, secure, and scalable production capability that fits into your end-to-end workflow and runs where you need it to.

Data
Sources
Load &
prep data
Develop
ML models
Wallaroo Production
ML Platform
Explore
Outcomes
Data Lake
DEPLOY, SERVE, OBSERVE, AND OPTIMIZE ML

From Python Notebook to real-world results, much faster.

(while you free up your data scientists’ and engineers’ time)

Deploy in seconds Self-Service toolkit to deploy and scale ML

Easy-to-use SDK, UI, and API for fast, repeatable, low-code/no-code ML operations

Scalability + performance Blazingly Fast Inference Server

Distributed computing core written in Rust-Lang uses up to 80% less infrastructure

Continuous Optimization Advanced Observability

Comprehensive audit logs, advanced model insights, full A/B testing

What makes Wallaroo.AI different?

Breakthrough speed and agility in the cloud or at the edge

Flexible integration with your tools and infrastructure

  • Integrates with your ML toolchain (notebooks, model registries, experiment tracking, etc.)
  • Intuitive APIs and Connectors for custom workflow integrations
  • Works with specialized ML acceleration libraries

Ultrafast Rust-based Server that lowers cost by 50% – 80%

  • 3X- 13X faster Batch Inferencing
  • Real-time Inferencing Latency as low as 1 microsecond
  • 5X more efficient data handling
  • Workload autoscaling

(As benchmarked with the ALOHA open-source model, various TF, XGBoost, and Computer Vision models in AWS, Azure, GCP, and Databricks)

Centralized model management, observability, and optimization

  • Collaborative Workspaces with access control
  • Automated feedback loop for ML monitoring and redeployment
  • Integrated Model Validation with A/B testing and Canary deployments
  • Easy-to-use, unified UI
Learn more about the Wallaroo.AI platform
Easy
  • Simple SDK and UI for Data Scientists
  • Works/integrates with customer’s toolkit
  • Deploy anywhere with minimal fuss
  • ML Monitoring and management to drive value
Scalable
  • Many models, many endpoints, many use cases
  • Lots of data
  • Complex models and ML pipelines
  • Scale with lower cost and overhead
Efficient
  • Lower resource requirements for ML Workloads
  • Quick resolution of ML model issues
  • Let the people you already have get more done
  • Fast time-to-value

Turbocharge your ML workloads in your own cloud, your customer’s remote cloud, or at the edge

Your Data Science /
ML Environments
Wallaroo
Operations Center
Your Cloud /
On Prem
Wallaroo
Server
Your Cloud /
On Prem
Wallaroo
Server
Remote Cloud /
On Prem
Wallaroo
Server
Edge
Locations
Wallaroo
Server
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