Artificial Intelligence Community

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Who we are

One of the youngest Communities

There’s no better place for you to grow. Let’s grow together!

We cover everything around AI

Data Analysis and exploration, Machine Learning model development & deployment

One of the highest growing Communities

Deep and wide knowledge base

Working with really experienced engineers

Great Chance to learn and share ideas

We are crafting AI Solutions

For clients from Fortune 500, in domains like Healthcare, Automotive, Fintech and Retail.

eXperience a true Sense of Community

There’s no better feeling than feeling like you’re at home, while at work.


Our AI Ecosystem

If you’re passionate about AI and Machine Learning, then our community is the right place for you, whether you’re a data scientist or a machine learning engineer. 


The technology spectrum is continuously evolving, so what matters the most is your drive to keep yourself up-to-date. 


Most of the projects that we tackle are now on Cloud and we usually build end-to-end AI solutions, using a variety of the below technologies: 

  • Cloud providers ML studios: AWS SageMaker, Azure ML Studio, GCP
  • Platform-specific models for : Android, iOS and Web Apps (Client-side inference)
  • Data preprocessing (depending on the type of data): Spark, Pandas, Numpy, OpenCV
  • ML Frameworks: TensorFlow, PyTorch
  • Model deployment: TensorFlow Serving, TorchServe, Custom endpoints (FastAPI/Flask)
  • Programming Languages: Python, C++
  • Reporting: Tableau, PowerBI, Dash


Do you have experience with machine and deep learning solutions? If you’ve been part of ML projects, you can join us as well and we’ll help you transition to newer machine learning technologies through our carefully crafted trainings.  


Projects where you can have an impact


One of our customers is a German Automotive Company. We help the company steer towards a data-driven, AI-led company, by implementing and maintaining ML models on their platform. Their main objectives are data democratization and the culture of self service. We’re talking about data from mileage, speed, consumption, RPM, engine faults, driver behavior, road driving patterns and car components that we need to process and carefully tailor for the machine learning models. To accomplish that, we’re using S3, Glue, Lambda, Kinesis, Athena, Codepipeline, CLI, PySpark and Terraform together with AWS SageMaker for the machine learning solutions. 


One other customer is a US food provider company that develops cutting-edge AI solutions in order to improve their processes, but also to reduce expenses from food waste. On the machine learning side we’re responsible for bringing the models developed, alongside the company scientists, from a proof-of-concept phase to large-scale training and deployment optimization using Python, Spark and AWS SageMaker.


Plans to rebuild the authentication, authorization, and SSO for the platform in order to resolve the existing performance issues are in the pipeline utilizing expertise from developers well versed in NodeJs, AWS Lambda, MongoDB, Redis, PostgreSQL.


Our latest customer within AI is from the FinTech space in the US, where we are developing a recommendation system that would keep users engaged on the company platform. Beyond fully understanding their business model and acquiring business knowledge, we innovate through our models in order to understand the behavior of their users and provide relevant recommendations. We use Dataiku for the data integration and preprocessing while the machine learning models are being develop in TensorFlow.


Sense of Community