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You are already on the right track to optimizing the use of data power in your company.
However, we don't want to leave you alone with this.

MLOps Q&A and tutorials

❓ Is every node in the Vertex AI pipeline executed on a different machine?
❓ How to test a pipeline?

Marcin Zabłocki, a MLOps Architect will record a series of MLOps tutorials and a Q&A that will be available soon.

COMING SOON

(You will receive an email notification from us about new MLOps materials)

We encourage the ongoing development and introduction of the latest and best MLOps practices,
so from us you will receive:

Just to be clear, whether you need our technical support or not, we will equip you with the best knowledge and expertise in this area.

You can always opt out of receiving these emails, but for now, trust us. Once you see what's inside you will just want more .

A series of emails with selected top MLOps tips. Only valuable, meaty content.

An invitation to the following webinar: Building Machine Learning pipelines with Kedro and Vertex AI on the Google Cloud Platform, hosted by Michał Bryś - Senior ML Engineer and Technical Product Owner

An invitation to a demo presentation of the MLOps Platform - you will find out what elements a well-functioning platform consists of and what the main principles of its operation should be

For 4 years GetInData has been building Machine Learning Platforms for dozens of clients such as PLAY - the biggest Polish telecom or ING Bank with over 14.1M primary customers from over 40 different countries. However, we were building data lakes and other big data solutions long before then.
We have developed projects that have brought tangible benefits to our clients (from small startups to the biggest companies on the market) by accelerating the Machine Learning processes, e.g.:

For ING Bank we reduced data discovery time by 30%, transferred the servers’ layer to the platform as xrdp containers in 5 months, meeting the regulations of over 40 different countries' markets. Download the customer story to get more insight: ING Customer Story.

For PLAY we delivered architectural guidance and navigated the project from the PoC phase to successful full scale deployment in production. As a result, PLAY is currently using a scalable, secure, extensible Data Platform that can easily be queried for analytical, business and marketing purposes in real time, with a reduced operational cost. Download the customer story to get more insight: PLAY Customer Story.