Productionizing AI at scale

It is only in production that AI adds clear and measurable value. Only by implementing AI across the enterprise and at scale, will organizations be competitive for the next decade.

Grace AI Platform & AI Governance

Meet the Grace Platform

Grace standardizes processes and workflows across such areas as data ingestion, model training, -deployment, -monitoring, -life cycle management, and retraining. Grace provides organizations with Ethical AI, including data- and model monitoring, surveillance as well as traceability, explainability, and other AI compliance measurements.


Efficient and productive AI implementation with the Grace AI Platform


Standardizing processes and improving workflows in the data science functions for organizations seeking to implement AI.

Grace AI Platform flexibiliity


Full flexibility to freely install new libraries, and the choice to work with individually preferred data science tools, is most often a key prerequisite for ambitious data scientists of today. 

vendor independent AI platform


Vendor neutrality: supporting Microsoft Azure, Google Cloud Platform, Amazon Web Services, as well as on-premise installations and hybrid options.



Focused on compliance and GDPR, supporting all the necessary InfoSec and IT security features as required in most organizations. Offering organizations to apply their own security and privacy features.



Ensuring that all activities are traced, explained, and enforced. This includes all areas within the data science model development, data used for model training and development, model bias and more.

Why an AI Platform?

To transform you need to go all the way

Too many data science and AI projects stay in the sandbox. In larger organisations the frequent problem is that you have a lot of data – but what do you get out of it? You need to be able to transfer the area of intellectual interest to actual integration, production, and operations. That is where the real value of AI is!

“An AI platform basically lowers the barrier of entry and enables fewer engineers to reinvent less, allowing them to focus on implementing AI that is specific to the business.”

Danny Lange

Board Member and Shareholder, 2021.AI

In-house data science team

The Grace Platform offers clients with in-house data science teams an enterprise AI solution to support and enhance team productivity and efficiency, as it standardizes processes and workflows across the data science functions.

No in-house data science team

The Grace Platform offers clients without in-house data science teams a fully functional AI solution, where the full AI life cycle can be run as a Managed Service from 2021.AI. Enabling organizations of all sizes to embark on the AI journey.

Technology companies

We offer AI ambitious technology companies to integrate Grace Platform to their current architecture and infrastructure, offering a shortcut to state-of-the-art AI technology.

In such engagements, we can take responsibility for AI model development, offering a fast track and low risk route to advanced AI technology and AI models for such companies’ end-clients.

Grace Platform

Core components

data ingestion


Grace supports a variety of structured and unstructured data, as well as streaming data.

AI model development


Managing the entire model development and production life cycle. 



Based on Kubernetes infrastructure, Grace deploys models in docker container offering to run and manage them inside or outside of the Grace AI Platform and infrastructure.

Grace AI Platform - Development and Production

Get in touch

Ready to transform your business and take AI into production?