Service
Data Platforms
Build the data layer modern AI demands. Lakehouse, streaming, governance.
Typical engagement: 10–20 weeks
Overview
Modern AI demands a modern data layer. We design and build lakehouse, streaming, and governance stacks that hold up under real query volume, real privacy review, and real cost pressure.
What we do
- Reference architecture using open formats (Iceberg, Parquet, Delta) — no vendor lock-in.
- Streaming + batch ingestion with schema evolution and replay.
- Data governance: lineage, access control, PII detection, retention policy automation.
- BI and ML enablement on the same substrate — no parallel pipelines.
Outcomes
- A production data platform powering at least one downstream BI dashboard and one ML model.
- Documented governance posture suitable for PDPA / MAS audit.
- Cost model showing per-query and per-pipeline economics.
Fit for
- Companies with data scattered across SaaS systems and OLTP databases who want one truth.
- Teams committed to building ML or analytics products on internal data.
Not fit for
- Companies whose entire reporting need fits in a spreadsheet — we'd be over-engineering for you.
Data Platforms
Want to talk about data platforms?
Tell us briefly what you're trying to achieve. A partner will reply within one business day.