Modern data stack


Snowflake foundation and migration

Moving off legacy warehouses, SQL Server/Postgres, or a stack of scheduled spreadsheets; roles and access, dev/prod environments, warehouse sizing and credit guardrails so the bill never surprises you


dbt and GitHub engineering

Modular models, automated tests, generated documentation, column-level lineage, pull-request review, and CI that catches a broken model before your CFO does


AI enablement

AISQL functions for classification, extraction and summarisation; Cortex Search for retrieval over your own documents; Cortex Analyst for plain-English questions — all inheriting the permissions you already have

If two people in your company can produce two different revenue numbers, you don’t have a reporting problem — you have a lineage problem

We put your Code/SQL business where it belongs: in Git, tested, peer-reviewed and traceable end to end.

Snowflake as the engine, dbt for modelling and tests, GitHub for review and CI — so every figure on every dashboard traces back to the row it came from and the change that produced it.

Once that foundation holds, Cortex AI runs models directly on governed data: no extracts, no separate vector database, nothing leaving your account.