AI/ML & DATA

ML Engineering

Build & Optimize Scalable ML Pipelines
for High-Impact Data-Driven Decisions.

HOW IT WORKS

Your data is more than just a collection of numbers—it’s a vital resource that, when harnessed correctly, can drive strategic decisions and competitive advantage. Our comprehensive AI/ML Engineering services are designed to ensure your data does exactly that.

From meticulous Data Engineering that organizes your data to Data Analytics that reveals clear insights and actionable predictions, we help you stay ahead in a rapidly evolving market.

CloudGeometry GitOps Lifecycle for Data engineering

We specialize in engineering data systems that transform raw data into actionable insights. CloudGeometry doesn't just move and store data; they build robust architectures, including modern data lakehouses, ensuring your data is accurate, accessible, and ready to fuel decision-making.

By working with Databricks to integrate the scalability of data lakes with the performance of data warehouses, CloudGeometry's lakehouse solutions enable us to unlock the full potential of your data, driving innovation and efficiency across your organization.

Rob Giardina — Founder, Claritype
Rob Giardina
Founder, Claritype

Knowledge Management & Extraction

Before you can do anything with your data, you need to know what you have and how to get to it efficiently. We’ll provide data engineering services that help you audit your data sources, store them efficiently, and make sure they’re usable when you need them.

Data analytics

Data analytics uses advanced tools to explore large datasets, revealing trends, patterns, and insights. We’ll help you use it to make smarter decisions, optimize your operations, and improve efficiency across various functions such as marketing, finance, and operations.

Lakehouses

A lakehouse combines the best of data lakes, which are vast storage systems that hold a wide range of data, from structured to unstructured, at any scale, with data warehouses, which provide atomic transactions and other data management features. We’ll help you use lakehouses to find and store all of your data, and to use it to do analysis across multiple data types so you can make the best possible decisions.

ML Engineering Services

CloudGeometry provides a comprehensive suite of ML engineering services, focused on helping organizations harness the full potential of their data through advanced machine learning techniques.

A central aspect of our approach is the implementation of the medallion architecture, a structured and layered framework that optimizes data processing and pipeline organization. This architecture, composed of bronze, silver, and gold layers, enables the incremental refinement and enrichment of raw data, resulting in scalable, efficient, and reliable ML pipelines. With this architecture, CloudGeometry ensures that your ML solutions are not only robust and scalable but also flexible enough to adapt to your organization’s evolving needs.

Laying the foundation for Artificial Intelligence / Machine Learning

Data engineering lifecycle

Generation
Ingestion
Transformation
Serving
Data Storage
Analytics
Machine learning
Reverse ETL

Undercurrents:

Security
Data management
DataOps
Data architecture
Orchestration
Software engineering
Artificial Intelligence / Machine Learning requires attention to details such as the compute environment, storage, and software infrastructure. Includes directly related components, such as the ingestion and transformation of data and model serving, and indirectly related, like security and orchestration.
Austin Health
Austin Health utiliez Delta Lake to provide a robust data solution for huge data merges, reducing complewhen integrating with their electronic health record (EHR) system for data reporting, patient contact & data flow.
Disney
With our lakehouse, Disney was able to unify subscriber data & streaming data on an open platform to efficiently build personalization ML models.
GE Digital
GE Digital, a pioneer in the Industrial IoT (IIoT) landscape, wants to harness the power of IoT data streams to drive digital transformation across various sectors of the global economy. This task involves integrating vast amounts of data from diverse sources, ensuring real-time processing, and providing actionable insights, all while maintaining data security and scalability.
Splunk
Real-Time Asset Intelligence and Remote Operations