Notebooks and pilots don’t make a production platform.
Production workloads need tested pipelines, governed access, release controls and monitoring. Most teams don’t have the time to build them alongside daily operations.
- Pilots that never become scheduled production jobs
- Pipelines without tests or release controls
- Governance that differs from workspace to workspace
- Compute costs growing with every new workload
Built in your Databricks workspace.
We build Lakeflow pipelines and Bronze, Silver and Gold data products, governed in Unity Catalog.
- Batch and streaming pipelines
- Unity Catalog governance and access
- Delta Lake performance and lifecycle
We build the agent with Agent Bricks, on governed data in the same workspace.
- Agent Bricks and model serving
- ML and GenAI data pipelines
- Evaluation and human review
We add the observability, testing and release controls that keep it in production.
- Monitoring and data-quality checks
- Testing, release and cost controls
- Fixes proposed as pull requests
From kickoff to your first use case in production on Databricks.
Everything runs in your workspace, under Unity Catalog.
Business logic kept separate from platform plumbing.
Questions we hear
We already run Databricks. Where do you start?+
With a Production Sprint. We review current workloads, governance gaps and platform fit, pick the first use case and put it into production.
Will this lock us further into Databricks?+
No. We separate business logic from platform plumbing and use explicit contracts and portable interfaces. Databricks capabilities are used where they create real value, not as a reason to move every workload.
Can you connect Databricks to our other systems?+
Yes. We integrate with your existing cloud, BI, orchestration and operational systems.
Where does it run, and who controls it?+
Everything we build for you is yours: pipelines, data models, infrastructure code and documentation, in your own cloud account and repositories. Our agents and accelerators come with a licence that keeps working even if you stop working with us. If you need full source access, we offer that too.
What happens after the Sprint?+
You can run it yourself, extend it with a Build, or have us operate it with Managed.
Put your first use case into production on Databricks.
Tell us the use case and what you run on Databricks.