Databricks Gold Partner

Start your Databricks journey with us by establishing the data intelligence platform foundation, development practices and governance. Build solutions for BI reporting, natural language interaction with data (Genie), advanced analytics, agents, and AI use cases on Databricks. 

We design and implement Databricks Lakehouse and data intelligence platform architectures for enterprise and domain‑driven use cases, including unified platforms and data mesh architectures. We help organisations build scalable data ecosystems and data products using Databricks as the core platform. 

Well‑defined data modelling practices are essential for successful analytics and AI solutions. We help define modelling approaches aligned with business domains and use cases. While Databricks recommends the medallion architecture as a foundation, effective modelling depends on business context, analytics requirements and AI ambitions. 

Our Databricks‑native MLOps approaches help organisations move from experimentation to production‑grade, enterprise‑scale AI on the data intelligence platform utilising, for example, MLflow, Mosaic AI & Agent Bricks. We support the full lifecycle from opportunity identification and pilots to operationalised ML and AI solutions, using Databricks ML and AI capabilities.

• Create reusable, automated ML pipelines
• Standardise ML development and deployment practices
• Reduce technical debt and accelerate time‑to‑value 

To accelerate time‑to‑value, we provide Databricks Accelerators and Bricksbuilder solutions – reusable, production‑ready solution patterns built on the Databricks data intelligence platform.

These accelerators cover platform setup, data engineering, analytics, AI and governance, and are continuously refined through real customer projects. Our Bricksbuilder solutions combine Databricks best practices with our industry expertise, enabling faster delivery, lower risk and consistent quality across projects, especially in industrial, energy and financial services environments. 

Databricks Lakebase enables real‑time, data‑driven applications and AI systems by unifying transactional, analytical and AI workloads on the data intelligence platform. Together with Databricks apps, organisations can build and run governed applications directly on lakehouse data. We support Lakebase adoption from database modernisation to production‑ready applications and AI‑powered services. 

Migration is often the starting point for modern data and AI initiatives. We help organisations migrate legacy data warehouses, analytics platforms and data pipelines to the Databricks data intelligence platform in a structured, AI-powered, business‑driven way.

Our Databricks migration approach covers assessment, phased execution and optimisation. Typical migrations include legacy data warehouses and on‑premise or cloud‑native analytics platforms. Beyond technical migration, we use the transition to improve data models, governance, performance and AI readiness, ensuring long‑term value rather than a simple lift‑and‑shift. 

Good data governance improves efficiency, data quality and trust while reducing risk. We leverage Databricks‑native governance capabilities, including Unity Catalog, to govern data, analytics and AI across workspaces.

We help organisations:

• Govern multiple Databricks workspaces with centralised, fine‑grained access control
• Standardise development and operating models
• Support data mesh architectures with federated governance
• Enhance security, privacy and data quality monitoring