Scaling entreprise AI with MLOps

Together with Silo AI, you are able to modernize your machine learning operations, including continuous model development, testing, serving, and monitoring.

Success in the new age calls for experienced partners

We help you apply AI and take it into use even in the most complex environments with efficient MLOps processes and tooling.

With Silo AI, you get to work with some of the brightest AI Scientists and AI Engineers that have a strong track record in scaling AI to bring value for various business needs.

Our expertise

With our experience from 100+ production-level AI projects, we’re your trusted partner for

  • Planning and implementing DataOps environment,
  • building a robust Machine Learning Operations (MLOps) infrastructure to get full transparency on the machine learning training workflows,
  • evaluating and tailoring the AI models and algorithms for specific needs and use cases,
  • deploying AI/ML either on the device level, EDGE, or cloud, and
  • human in the loop-integration to your current processes, environments, and automation systems.

Reliable and scalable AI with MLOps

The biggest challenge in production-level AI is not finding the best ML model, but building a reliable, scalable, and maintainable system for operating it in production and developing it continuously.

We put our learnings from 100+ production-level AI projects into one easily digestible and visual eBook about scaling AI with MLOps.

Image of ML Ops architecture

MLOps is your key in scaling AI adoption across the company

The transformation into a truly AI-driven company requires meticulous engineering and a proper machine learning infrastructure. With that, you’ll ensure that the core solutions work optimally and deliver measurable results in a transparent way, while being connected to the rest of the digital systems of the company.

MLOps is a way-of-working that puts your people working around the machine learning solutions to the core of the process.


Building operational AI/ML with MLOps

In this webinar, we dived into the infrastructure and organizational requirements of getting real-time machine learning-driven insights and analytics, that help run your operations smoothly. With our invited guest Unity, we showed an example of how solid machine learning operations (MLOps) helps scale several machine learning products at once.

Experimentation culture of Netflix

Machine Learning is defined by a need for rapid experimentation. To achieve an environment of iterative and low-risk experimentation, both hard aspects (tools and platforms) and soft aspects (culture, ways of working) need to be aligned. Ville Tuulos, the driving force behind Netflix’s Metaflow platform, explains how Netflix has managed to tackle both sides of the coin.

Learn from our MLOps experts


Establishing MLOps practices for one of the biggest financial institutions in Sweden

I worked as a Solution Architect in building an MLOps platform that is offered as a service and aims to be the backbone for most of the ML operations in one of the biggest financial institutions in Sweden.


Implementing end-to-end scalable MLOps for a computer vision product

The overall goal of MLOps is to make the process of productizing ML models smoother. MLOps applies the DevOps techniques, concepts and practices to machine learning systems with an increased demand to take care of aspects around the activities, such as data versioning, data lineage and data quality. 


When is the right timing in setting up the MLOps practices?

We asked our Head of AI Solutions Alexander Finn to sum up the signs that indicate the need to start building a full-blown MLOps infrastructure and processes. Alexander is an expert in creating complete software development lifecycles for machine learning projects.

Contact Silo AI

Considering elevating your business with a robust MLOps solution? We recommend you get in touch early on to get the best value of our expertise and collaboration.

Why work with Silo AI?

Nordic’s foremost AI scientists live at Silo AI
We serve you with a strong academic pedigree and a track record of building real-world AI solutions and products.
MLOps helps organizations to scale AI usage
Silo OS customizable infrastructure and products
With 100+ production-level AI projects on our back, we’ve built tools that we can leverage for quick validations.
Long-term partnership to make you succeed
AI is not just scattered algorithms here and there. You need a partner to build a sustainable AI roadmap and infrastructure to bring AI-enhanced products to market.
We challenge you to ask why
We don’t only deliver projects but we challenge you to think differently.