Service 01

Data Engineering

If the system where your data resides is not robust enough, then you will spend amounts of time and money fixing and releasing new features. We design and implement robust data systems so you can confidently and cost-effectively store, consume and move your data around, without worrying about elevated costs, fear of breaking something or ad-hoc solutions. Our areas of expertise include:

Data ingestion

This means cleaning, converting, and organizing data so that other processes in the Data Lake or Ware House can utilize it.

Data processing & orchestration

From simple pipeline orchestrations to complex ones, transform data so business units can leverage it for their analysis.

Data storage

Manage and design cost-effective lifecycle mechanisms to store pre processed and post-processed data in a database, data lake or data warehouse.

Service 02

ML Engineering

Having proper MLOps engineering practices in place to experiment, test, develop and roll out ML models at scale is not optional but mandatory. We design and implement robust ML systems so your data scientists can focus on developing accurate models reducing time-to-market and bringing more value rapidly.
Our areas of expertise include:

ML Operations

Designing, implementing and maintaining a robust ML platform is key for data scientists, ml engineers and data engineers to work seamlessly so models can be released with ease.

Productionizing ML models

The ML lifecycle consists of many complex components such as data ingestion, prep, model training, tuning, deployment, monitoring and explainability.

Service 03

Data Analytics

Leverage data science and machine learning (DS/ML) to accelerate growth, improve predictability and enhance customer experiences. Our areas of expertise are:

DS/ML Applications

Time Series, Simulations and Optimizations, Recommender systems, Anomaly detection and GeoSpatial.

NLP Applications

Popular use cases of natural language processing (NLP) that enable businesses to gain value from unstructured textual data. Like summarizing content, extracting sentiment from customer reviews, chatbots, research assistance, fraud detection or content generation.

Price is what you pay, value is what you get.
Do you know what value you want to get? Contact us!

Why do we offer only these 3 services?

How does Data Engineering, ML Engineering and Data Analytics relate to each other?

Just like any house, if the foundations are not set, it’s impossible to gain any valuable insight about your data. Simply.

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