Lakehouse Architecture
One source of truth for analytics and AI.
A lakehouse done right replaces three different legacy stacks with one open, governed platform. We stand up the medallion model, the governance layer and the read paths that BI, data science and AI can all share.
10×
Storage cost reduction vs. DWH
<5 s
Trino query latency at petabyte scale
99.9%
ACID guarantee under concurrent load
3 layers
Medallion zones (bronze/silver/gold)
What we ship
Capabilities
Open-format lakehouses on Delta or Iceberg — bronze/silver/gold layers, ACID transactions and a single substrate that powers BI and AI from the same tables.
- 01
Delta Lake or Apache Iceberg
Open table formats with ACID transactions, time travel and schema evolution — no vendor lock-in, runs on your object storage.
- 02
Medallion (bronze/silver/gold) modelling
Raw ingestion, curated business entities and aggregated analytics separated into governed layers — every team reads from the right tier.
- 03
Object storage on S3 / GCS / on-prem
Runs on any S3-compatible store — AWS, GCP, Azure or MinIO on bare metal — at a fraction of proprietary DWH costs.
- 04
Time travel, schema evolution, ACID
Roll back to any past snapshot, evolve schemas without downtime, and guarantee exactly-once writes under concurrent load.
Outcomes
- Single source of truth for BI and AI
- Open formats — no vendor lock-in
- Cheaper storage and faster queries at scale
Tech we use
In the field
- 1
EAC telco data consolidation
5 country subsidiaries unified into one lakehouse — 80% storage cost reduction, single BI layer for group reporting.
- 2
Financial services data mesh
Retail bank migrated from Oracle DWH to Delta Lake in 4 months — analysts query petabytes in under 5 seconds.
- 3
AI training data platform
Lakehouse as the unified substrate for both BI dashboards and model training — same tables, governed access, no data duplication.
How we deliver
Our delivery process
Every engagement follows the same rigorous four-stage approach — so you know exactly what to expect, and when.
- Step01
Data landscape mapping
We inventory every source system, schema and access pattern — the lakehouse is designed around real read paths, not diagrams.
- Step02
Medallion layer design
Bronze ingestion jobs, silver business-entity models and gold aggregations designed with your data and analytics teams.
- Step03
Governance & access control
Column-level access policies, Unity Catalog or OpenMetadata wired in from the start — governance is not an afterthought.
- Step04
Migration & cutover
Parallel-run with your existing DWH until query parity is confirmed — cutover with zero downtime to BI consumers.
Ready to get started?
Build lakehouse architecture for your product
Tell us about your use case — we'll respond within one business day with a proposal scoped to your context.
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