Build Impactful AI/ML
‍For the Real World

Build serious AI and ML systems effortlessly,
scale and deploy them securely in your cloud

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Created at Netflix, perfected at leading orgs

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@trigger(event="data_update")
class TrainingFlow(FlowSpec):


    @step
    def train(self):
        self.df = self.load_data()
        self.model = train(self.df)

ML and AI are eating the world

Power your business with battle-hardened tools and infrastructure for custom ML and AI

Regional environments

Tala operates globally, securely separating regional deployments using Outerbounds perimeters

Flexible Workstations

Tala's data scientists and ML engineers develop their ML and data projects using Outerbounds cloud workstations

Advanced custom models

Artera develops advanced custom models for cancer diagnostics using Outerbounds cloud workstations

Scalable GPU cluster

The models require massive-scale GPU resources, running across multiple compute pools on Outerbounds

Flexible data processing and ML

Teams at Flexport use Outerbounds for ML, data integration, and for executing Python code at scale

Effortless operations with best practices built in

Flexport is able to ship more ML and data projects, quicker, without maintenance or engineering burden

Developer autonomy

Using Outerbounds, data scientists at Black Crow are able to develop, scale, anbd deploy ML and AI projects autonomously

Experiment tracking & versioning

To ship projects confidently, developers at Black Crow use the Outerbounds UI to observe models that are tracked and versioned automatically

Ship ML/AI projects faster with delightfully integrated, developer-friendly tools

Develop

First-class development experience for your ML/AI teams

Simple APIs

Workstations

GenAI

GitOps

Develop production-ready ML/AI systems with human-friendly, open-source Metaflow, created by us at Netflix, battle-hardened at thousands of leading organizations, backed by a vibrant community

Boost productivity with cloud workstations using familiar VSCode or notebooks, accessible locally or in the browser, securely hosted in your cloud. Develop code, host apps, and observe experiments in one environment

Leverage state-of-the-art LLMs and GenAI models, privately running in your account without per-token pricing. Customize models with fine-tuning, leveraging cost-efficient GPUs.

Seamlessly integrate CI/CD into your development workflows, offloading large-scale testing to the platform. Deploy pull requests and branches as isolated production experiments

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Scale

Never be limited by compute resources or cost

Scale Freely

Multi Cloud

Cost Efficient

Train models, large and small, process data, and harness GPUs running even thousands of tasks with a line code. Executing code in the cloud is a breeze with automatically baked Docker images

Blend instances from your AWS, Azure, and GCP accounts into unified compute pools. Include on-prem clusters and specialized providers like CoreWeave and the NVIDIA cloud in the mix

Compute is a commodity - say no to extra margins and hidden fees. Reduce cloud costs by leveraging your lowest-cost cloud instances, visualizing costs incurred at the level of individual functions

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Deploy

Build and operate production systems confidently

Production

Event-Driven Systems

Integrations

Deploy business-critical systems on a fully managed platform with zero-downtime upgrades, guaranteed SLA. Built with the same components and experience that powers AI and ML at Netflix

Compose robust systems out of modular components that react to events in real-time. Deploy workflows for ETL, continuous training, batch inference, and data processing with ease

Connect to data warehouses, existing microservices, and 3rd party tools securely with built-in integrations. Control access with granular RBAC and perimeters, leveraging your existing security policies

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Delightful developer experience covering the full stack of ML and AI

On robust infrastructure, endorsed by platform engineers

Outerbounds follows the Bring-Your-Own-Cloud model: All data, metadata, and compute stays in your cloud accounts.

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Blend compute resources from major clouds, AWS, GCP, and Azure, as well as on-prem clusters and specialized providers like the NVIDIA cloud and CoreWeave.

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Access data securely from data warehouses and lakes, respecting your existing permission boundaries. Trigger workflows automatically when data updates.

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All code, data, and models are versioned and tracked by default. Monitor systems with custom visualizations and integrate with your existing observability tools.

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Define securely isolated environments for production, staging, or different teams or regions, each with environment-specific roles and policies.

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Provision fully integrated cloud workstations securely in your environment. Access them in the browser or through a custom VSCode extension.

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Compose arbitrarily complex systems from modular workflows connected through events. Deploy them confidently in isolated namespaces.

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Build AI systems with LLMs and other GenAI models, securely running in your environment without per-token pricing.

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Fully managed with zero-downtime upgrades, automatic scalability, and dedicated support - and a guaranteed SLA.

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Stop paying extra margin on cloud compute. Attribute and reduce costs with built-in cost optimization views.

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Join happy humans building
smarter machines

Join our Slack community

With Outerbounds, the team has shaved months off the time it takes to ship a productionized machine learning model!

Metaflow lets us test hypotheses faster than ever—speed is critical in AI, and Metaflow delivers

Kevin McEntee

SVP Engineering

Equilibrium Energy

The developer experience is great; we love how fast we can iterate, and the code looks clean—it’s just Python.

Santosh Jha

Software Engineer, AI Infrastructure

CloudKitchens

Thanks for Metaflow: it's a pleasure to use!

Laure Vancau

Biomedical Data Engineer

Swiss Data Science Center

I really appreciate the clean syntax and the seamless transitioning from dev to dev-at-scale to prod-at-scale

Fabien Pertuy

Machine Learning Principal Scientist

Sanofi

With Metaflow, we were able to test twice as many models in a single quarter as we did in all of previous year!

Kelly Davis

Software Engineer

Read Case Study

I really appreciate the clean syntax and the seamless transitioning from dev to dev-at-scale to prod-at-scale

Fabien Pertuy

Machine Learning Principal Scientist

Thanks for a fantastic product ❤️

Sam Thelin

Principal AI Scientist and Technical Lead

Metaflow is such an amazing tool!

Ben Brandt

Software Architect

Metaflow has really been helping in speeding up our ds workflows!

Utkarsh Vashisth

Machine Learning Engineer

Been using metaflow for a while now, and love it. At its best, it hugely speeds up our development cycles

Harvey Pratt

Chief Executive Officer

The Promenade AI

Outerbounds has proven to be transformative for us. The platform has allowed us to execute and train models without the burden of worrying about infrastructure

Soma S Dhavala, PhD

Director

Wadhwani AI

In six weeks, a team that hadn’t used Metaflow before was able to build an ML-based model, A/B test its performance, which handily beat the old simple approach, and roll it out to production.

Thanasis Noulas

VP of Engineering

Trade Republic

Built with the core idea of allowing ML engineers and data scientists to use Python as native way to work, this friendly approach has tremendously boosted Carsales productivity in ML

Samuel Than

Senior MLOps Engineer

Carsales

After adopting Metaflow, we were able to ship eight additional models in just ten months, whereas before it took many more months to launch a single model!

Peyton McCullough

Staff Software Engineer

Read Case Study

Been using metaflow for a while now, and love it. At its best, it hugely speeds up our development cycles

Harvey Pratt

Chief Executive Officer

Outerbounds has proven to be transformative for us. The platform has allowed us to execute and train models without the burden of worrying about infrastructure

Soma S Dhavala, PhD

Director

In six weeks, a team that hadn’t used Metaflow before was able to build an ML-based model, A/B test its performance, which handily beat the old simple approach, and roll it out to production.

Thanasis Noulas

VP of Engineering

Built with the core idea of allowing ML engineers and data scientists to use Python as native way to work, this friendly approach has tremendously boosted Carsales productivity in ML

Samuel Than

Senior MLOps Engineer

Reproducibility and compliance were critical for us in the lending industry, and Outerbounds delivered that seamlessly!