Databricks that doesn't get stuck in the proof of concept .
We build your lakehouse on Databricks – from landing zone through Unity Catalog to a productive ML or GenAI use case. As a certified partner with 300+ data & AI projects behind us.
- 90
- days to production
- 300+
- data & AI projects
- 100 %
- infrastructure as code
- 3
- clouds: Azure, AWS, GCP
One platform for data engineering, BI and AI
Databricks is the right choice when data volumes grow, streaming comes into play and machine learning should be more than a notebook. Open formats instead of a dead end.
Delta Lake as an open foundation
Your data stays in open formats in your own storage – with ACID transactions, time travel and no proprietary dead end.
Unity Catalog for governance
Access rights, row-level security, lineage and audit in one central place – across workspaces and clouds.
Scale without a rebuild
Batch, streaming and ML run on the same engine. Growing data means more compute, not a new architecture.
AI right on your data
Model serving, Vector Search and Mosaic AI sit right on the lakehouse – GenAI assistants work on verified company data.
What we build for you on Databricks
From the first architecture decision to operations: one team for platform, data model, BI and AI – no handover losses between three vendors.
Platform & landing zone
A production-grade Databricks setup that considers security, cost and operations from day one.
- Workspace design, networking and Private Link
- Terraform modules for environments and permissions
- Unity Catalog with catalog, schema and role concept
- CI/CD with Databricks Asset Bundles
Data engineering
Medallion architecture with robust pipelines instead of hand-written one-off scripts.
- Ingestion from SAP, Salesforce, MES, IoT and files
- Delta Live Tables and Structured Streaming
- Data quality rules and monitoring
- Gold data products with documented metrics
Machine learning & GenAI
Models that actually make it from the notebook into production.
- MLflow, Model Registry and Feature Store
- Model serving including monitoring and drift detection
- RAG assistants with Vector Search on your own data
- Forecasting, predictive maintenance and quality analytics
BI & self-service
Analytics that business teams and management can both rely on.
- Right-sized Databricks SQL warehouses
- Power BI on certified semantic models
- Genie spaces for natural language questions
- Alerting instead of monthly surprises
Migration & modernisation
Replace existing landscapes without putting daily operations at risk.
- Migration from Hadoop, Synapse, Oracle or legacy DWH
- Parallel operation with metric reconciliation
- Step-by-step replacement instead of a big bang
- Takeover and clean-up of existing workspaces
FinOps & operations
Cost transparency from day one – Databricks gets expensive fast when nobody is watching.
- Serverless and cluster sizing with auto-termination
- Cost reporting per workload and department
- Runbooks, alerting and on-call support
- Enabling your team all the way to handover
Why companies choose us for Databricks
We are a certified Databricks partner and have worked productively on the platform for years – in manufacturing, retail, finance and healthcare.
- Certified data engineers, ML engineers and solution architects in a permanent team – no revolving freelancers.
- We don't sell licences. Our recommendation follows your workloads, not commissions.
- Every project starts with a business case: we quantify the benefit before the first euro of platform cost.
- Enablement is part of the deal – we build up your internal know-how and make ourselves redundant by design.
Typical Databricks projects from our practice
Production data from MES into the lakehouse
Machine and quality data land in the lakehouse in near real time; scrap causes become visible per shift instead of in the monthly report.
Scrap analysis in minutes instead of weeks
Group reporting from a single source
ERP, CRM and logistics data are merged into one certified gold model that Power BI reads exclusively.
–70% effort in monthly reporting
GenAI assistant on company knowledge
Contracts, manuals and tickets become searchable via Vector Search; answers come from verified data with source references.
Answers with evidence instead of hallucination
From decision to a productive data product in 90 days
Assessment & target picture
We review sources, workloads and skills, prioritise use cases and calculate the business case.
Landing zone & Unity Catalog
Workspaces, networking, permissions and CI/CD as code – production-ready, not a playground.
First data product live
One domain from bronze to gold including reporting or a model – in real operation, with real users.
Scale & hand over
More domains, FinOps routine and training for your team until they can develop independently.
Might Microsoft Fabric fit better?
If Azure and Microsoft 365 are a given and BI is the focus, Fabric is often the faster route. We are at home in both worlds.
Frequently asked questions
Do we need our own Databricks team?+
Not to begin with. We deliver architecture, build and operations, grow your know-how in parallel and hand over responsibility as soon as you are ready.
How do we keep costs under control?+
From the start we use serverless and cluster policies, auto-termination, budget alerts and per-workload cost reporting. Cloud cost is part of the architecture for us, not an afterthought.
Can you take over an existing Databricks environment?+
Yes. We run a platform review, clean up governance, cost and pipelines, and then take over operations or further development.
What about GDPR and the EU AI Act?+
Access concept, lineage, deletion processes and documentation are part of our standard scope. For AI use cases we also assess the EU AI Act risk class.
45 minutes with architects – not with sales.
We look at your starting point, sketch a Databricks target architecture and tell you honestly whether the effort pays off.
- Result: architecture sketch and rough effort estimate
- An honest view on whether Databricks or Fabric fits better
- Free and non-binding