Wallaroo facilitates the last-mile of your machine learning journey, getting ML into your production environment to impact the bottom line, with incredible speed and efficiency.
We provide a simple, secure, and scalable deployment capability that fits your end-to-end workflow.
Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage ML in production, unlike Apache Spark, or heavy-weight containers
ML models in seconds with a single line of Python code and/or a flexible API
ML with up to 80% lower cost and easily scale to more data, more models, more complex models
and identify sources of model underperformance and production bottlenecks in real-time
live models based on the latest data and insights with no downtime
No need to replace your data platform or change the popular tools your data scientists use to build models.
Easy-to-use SDK, UI, and API for data scientists and ML engineers to deploy, manage, and collaborate
Distributed computing core written in Rust-Lang for breakthrough scalability and performance
Stream of comprehensive audit logs + advanced model insights to drive results
Unlike Apache Spark or heavy-weight containers, Wallaroo was built from the ground up for ML in production.
- Designed for data scientists and ML engineers alike.
- Intuitive UI and dashboards.
- API enables flexible application & workflow integration.
- Efficient event-by-event runtime engine for batch or streaming analysis.
- Ideal for big data or fast data.
- Supports high-throughput, latency in the microseconds.
- Experimentation, A/B testing, and champion/challenger.
- Data validation, model anomaly and data drift alerting.
- Production audit logs for deeper analysis and compliance.
- Plugs into your on-prem and cloud data environment.
- Your data scientists can keep their popular ML frameworks.
- Single uniform deployment for diverse enterprise teams.
Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage ML in production, unlike Apache Spark, or heavy-weight containers,
Process tens of million of events per second in real-time to optimize individual ad auction bids
Efficient compute engine to run computer vision models at the edge
10,000 location-specific Dynamic pricing models
Analyze billions of daily events with sophisticated neural network models
Stay up to date on our latest news, case studies, how-tos, and events by visiting our blog.
Solve the 3 Challenges that Prevent Your ML from Driving Results
Download the Guide
