Data platforms that scale with your business
Lakehouse platforms, reliable pipelines and observability, built on the cloud you already run.
Our approach
We design and build the data platform your analytics and AI run on: lakehouse architecture, pipelines you can trust, and observability so you know when something breaks before your team does. We build on the platforms you already run, Snowflake, Databricks, AWS, Azure or Google Cloud, and hand back something your team can own and extend.
Lakehouse Architecture
Medallion-layer platforms on Snowflake, Databricks, AWS, Azure or Google Cloud that separate raw, cleaned and business-ready data so every downstream consumer works from a consistent source.
Reliable Pipelines
Ingestion, transformation and quarantine patterns designed for schema drift, late-arriving data and partial failures, so the platform keeps running when the source systems misbehave.
Observability
Freshness, volume and quality signals wired into the pipelines from day one, so your team knows something has broken before the business does.
Onshore, Senior Delivery
Senior engineers working inside your environment, under your governance, building for production and steady-state operation so the platform holds up after handover.
What's in the way
Most AI and analytics work stalls on the foundation. Data is spread across systems that don't connect, pipelines break, and no one trusts the numbers. You cannot put agents or models on top of data you cannot rely on.
How we deliver
Senior engineers who have built this before, working onshore and inside your environment, under your governance. We build for production and steady-state operation, so the platform keeps running on routine care.
When to bring us in
The first step for organisations whose data is fragmented or whose reporting is slow and manual. It is the foundation the semantic layer, agents and Xavier sit on. Get this right and every downstream program moves faster.
What you'll see
Foundation in months
Data and analytics infrastructure built from the ground up, ready for models and reporting.
Built for steady state
Pipelines and observability designed to run on routine care, so the platform holds up after handover.
Yours to own
Built on the platforms you already run and handed back with the documentation your team needs to extend it.
The value you've brought the organisation in the last 5 months has already paid off the expense and I'm excited to continue working together next year.
Jacqueline Lejarzo
Head of Data, Garvan Research Foundation
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Common questions
What is data platform consulting?
Data platform consulting is the design and build of the foundations your analytics and AI run on: lakehouse architecture, reliable pipelines, and observability. Xephyr builds platforms that scale with the business and stay maintainable on routine care after we hand them back.
What is a lakehouse architecture?
A lakehouse combines the low cost and flexibility of a data lake with the structure and performance of a data warehouse in one platform. It lets you run analytics, BI and machine learning on the same governed data without copying it between systems.
Can you work with our existing data stack?
Yes. We build on the platforms you already run, including Snowflake, Databricks, AWS, Google Cloud and Azure, rather than forcing a rebuild. The goal is a platform your team can own after we leave.
Ready to transform your data?
Book a call with our team to discuss how data and AI can drive results for your business.