Services Evolved from DataOps
Data & AI Platforms
AI is only as good as the data behind it. We build platforms that make data trustworthy, governed and ready for analytics and AI — and we still care about the small details, down to the execution plan.
What we do
- Modern data architecture
- Lakehouse, data mesh and data products on Databricks, Microsoft Fabric, Snowflake, Oracle Autonomous Database or BigQuery.
- Data engineering
- Batch and streaming pipelines (Kafka, Spark), ELT with dbt, orchestration with Airflow or Dagster.
- Metadata-driven and AI-assisted pipeline generation
- The evolution of our metadata-driven data warehouse approach.
- Data warehouse modernization
- Legacy DWH and OLAP estates migrated to a cloud lakehouse without losing history.
- Data quality, observability and data contracts
- Problems caught at the source, not in the board report.
- Governance and privacy
- Catalog, lineage, access policies, masking and pseudonymization, GDPR.
- Semantic layer, BI and self-service analytics
- Including natural-language questions over governed data.
- AI-ready data
- Vector stores and feature pipelines for RAG and machine learning.
- Database engineering
- Performance tuning, high availability, disaster recovery and patching.
What you get
- One trusted version of the truth
- Faster reporting
- Data your AI initiatives can rely on
Talk to a data architect.
Tell us where you are. In 30 minutes we'll tell you honestly what we'd do first — and what we wouldn't do at all.
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