Operationalizing Data Science™

ML is cool. Metis Machine actually gets it into your products.


Building a model is only
the beginning…

We understand wrangling infrastructure within your Data Science workflow can be even more frustrating than wrangling data. We also know how time consuming it is to develop and deploy machine learning pipelines at scale. We searched for tools that could scale with our workflow, and found the market wanting.

So we built Skafos.

Data Science Teams

We believe that data science teams need a better, faster, more efficient way to bring their data insights to life.

Skafos machine learning platform provides data scientists with an end-to-end support throughout the machine learning lifecycle, maximum tool & framework interoperability, real-time insights, and the ability to be up and running with our cloud-based production scale infrastructure instantaneously.

Skafos is the collaborative platform that removes the friction from machine learning deployment and management.

What would you build if your model wouldn’t break?

Data Scientist

Deliver Machine Learning with confidence.


Break Down Barriers

There is an emerging machine learning operations lifecycle. To effectively serve data scientists as they bring their insights to life, we provide the platform that facilitates maximum collaboration and cooperation between data scientists, engineers, and business analysts.

Optimize Speed to Market

Data scientists succeed when they provide an optimal return on investment and gain data insights instantaneously. It’s imperative that data scientists have access to production scale cloud-based infrastructure and optimize their speed to market in every way possible.

Deliver Real-Time Insights

Data science must be a real-time endeavor to achieve its full potential, and as such our platform delivers real-time insights through live job monitoring and alerts, to ensure our customers have the maximum confidence & visibility when implementing their data science initiatives.

Many of us who work in software know the panic on the other end of that 3am wake-up call: a production system is down. If you don’t know that feeling, just ask your DevOps or IT guy and watch them sweat. When different micro-services work together to deliver a product, things break. This contrasts with how Data Scientists …
by Tyler Hutcherson
At Metis Machine we build machine learning systems. These systems tend to be distributed in nature and require more data than you might imagine. Occasionally, the partitions the data lives on become unavailable for different reasons; third party router drops, software upgrades, etc. Therefore, consistency must be maintained …
by Jeremy Tregunna


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