One governed platform for every workload.
We design and build data lakehouses that replace the warehouse-versus-lake trade-off with a single governed copy of your data — open table formats, medallion layers, and the pipelines and controls that keep it trustworthy. Delivered near-shore by senior architects across the US and Latin America, on your cloud or on-prem.
A lake nobody trusts is a liability.
Data lakes were supposed to end the silos. Most created a new one: cheap storage nobody can vouch for, ringed by warehouses that cost more every quarter and pipelines only one person understands. A lakehouse fixes the architecture — open storage with warehouse guarantees — but only if the governance, quality and operating model are built with it. That is the part we do.
Four ways we build and fix lakehouses.
Greenfield Lakehouse Build
From nothing to production: platform, medallion layers, ingestion, orchestration and the governance model — designed as one system rather than assembled later.
- Bronze / silver / gold
- Delta & Iceberg
- Orchestration
Migration & Modernization
Move off legacy warehouses, Hadoop and sprawling ETL — workload assessment, phased migration, parallel run and a cutover your business does not feel.
- Workload assessment
- Phased migration
- Parallel run & cutover
Governance & Quality Layer
Make an existing platform trustworthy: catalog, lineage, access control and data quality wired in so analytics and AI run on data you can stand behind.
- Catalog & lineage
- Access & security
- Data quality
Streaming & Real-Time Ingestion
Change data capture from operational systems and continuous streams — including plant telemetry from the industrial edge — landing continuously and reliably.
- CDC from source systems
- Streaming pipelines
- Edge telemetry
Layers you can point at.
From scattered data to one governed platform.
Understand
We start with the workloads you actually run and the data behind them — never the technology first.
Architect
Senior architects design the target lakehouse end to end: layers, formats, governance and cost model.
Deliver
We build ingestion, transformation and quality pipelines with engineering discipline and tests.
Operate
Managed services keep the platform reliable, governed and cost-efficient long after go-live.
Fortune 100 operatorsDelivered for Fortune 100 oil & gas operators and enterprise clients across Latin America and the United States.
20+ yearsTwo decades architecting, building and operating enterprise data platforms.
Certified in-houseAWS, Azure, Databricks, Snowflake and Inductive Automation certifications held by our own architects.
Lakehouse implementation — answered.
What is a data lakehouse?
A lakehouse combines the low-cost, open storage of a data lake with the reliability, governance and performance of a data warehouse, so analytics and AI can run on one governed copy of your data instead of many disconnected silos.
How long does a lakehouse implementation take?
It depends on how many source systems and workloads are in scope. We deliver in increments rather than one big bang: a first governed layer serving a real business workload, then expansion. You see working software early, not a design document.
Do we have to migrate everything at once?
No. We assess workloads, migrate in phases, and run old and new in parallel until the new platform proves itself. Cutover happens per workload, so the business never depends on a single switch.
Databricks or Snowflake — which should we use?
Both are strong, and the right answer depends on your workloads, existing cloud, team skills and cost profile. We are certified on both and on AWS and Azure, so the recommendation follows your requirements rather than our bench.
Let's build the platform your data deserves.
Talk to a senior architect about your lakehouse roadmap.