Services
Data Platforms
Pipelines, lakehouses, and real-time analytics.
How we approach it
Data platforms fail socially before they fail technically: nobody trusts the numbers. We build lineage, quality gates, and ownership into the substrate so every dashboard can answer 'says who?'
Tools of the trade
- Kafka
- Databricks
- Snowflake
- dbt
- Apache Iceberg
- Algoryq Grid
What you get
- 01
Streaming and batch unified on one governed substrate
- 02
Self-serve analytics with lineage and quality gates
- 03
Real-time decisioning at production SLAs
How we deliver
01
Discover
Two weeks inside your domain. We leave with the problem stated in one sentence.
02
Architect
Systems designed on paper first — reviewed, costed, and stress-tested before a line is written.
03
Build
Weekly shippable increments. Production quality from the first commit.
04
Ship
Progressive rollout with observability, runbooks, and rollback rehearsed.
05
Evolve
We stay through scale — measuring, hardening, compounding.
Adjacent capabilities
