Snowflake, implemented properly.
We build Snowflake data platforms for small and medium businesses — ingestion, modelling, governance, AI and the apps on top. Melbourne based, working with teams across Australia.
Platform ready, one or two sources ingested
No bespoke orchestration to maintain
Runbooks, code and access, all yours
Everything between the source system and the answer
Greenfield Snowflake builds, sized for small and medium businesses. Most start with the foundations and add the rest as you need it.
Lakehouse foundations
Account, warehouse and role design, network policy, cost guardrails and a deployment pipeline your own team can run.
Platform build →
Data engineering
Ingestion with Snowpipe and Streams, modelling in dbt, orchestration in Tasks — tested, documented and observable end to end.
Pipelines →
AI and Cortex
Retrieval, summarisation and forecasting on data that never leaves Snowflake, with evaluation you can point at before it goes live.
AI on your data →
Data apps
Streamlit in Snowflake and Native Apps: the tool the operations team opens every morning, sitting on the model you already trust.
Apps and Streamlit →
Governance and cost
Horizon, masking and row access policies, lineage, and warehouse sizing that stops the bill surprising you at the end of the quarter.
Governance →Four steps, no surprises
Three weeks, the same shape every time. You see the platform working in week two, and you own it at the end of week three.
Assess
We look at your systems, reports and goals, then agree what the platform has to do first.
Design
Account, roles and data model on paper, reviewed with you before anything gets built.
Build
The platform stood up and your first one or two sources ingested and modelled, against real data.
Hand over
Documentation, monitoring and walkthroughs with your team. You own the platform and it runs without us.
Weeks, not quarters
Speed comes from preparation, not shortcuts. Most of the hard thinking was done before your project started.
Templates, not a blank page
Account setup, roles, pipelines and the dbt project come from templates refined over many builds. You start from something proven.
A defined scope
We agree up front what goes live: the platform and one or two sources. No open-ended discovery, no scope creep.
Years on Snowflake
The decisions that slow a first-time team down are ones we have already made, many times over.
Snowflake does the heavy lifting
Fully managed SaaS: no servers, patching or capacity planning. Storage, compute, security and AI in one platform means less to build and less to run.
One account, from source to answer
Data lands once, is modelled once, and is served to everything downstream from the same governed tables.
Governance, lineage and cost controls apply across every stage — not bolted on at the end.
Put AI to work, governed and trusted.
A Snowflake platform built so AI works on data you can stand behind: secured, governed and yours. Tell us what you want from it.