Snowflake is where most of our platform work lands: warehousing, governance, semantic views, and AI with Cortex. As a Snowflake Select Partner, we implement it, tune it, govern it, and keep its costs honest.
The situations we’re brought into
Evaluating the move
You’re choosing a cloud data platform and want an honest read on fit, cost, and effort, not a pitch.
Running like an expensive database
Snowflake is live, but it’s a few dashboards on raw tables: no governance, no semantics, no AI.
Spend keeps climbing
The monthly bill grows and nobody can point to which warehouses or queries are responsible.
AI, inside the perimeter
Leadership wants AI on company data, and security wants it to never leave the platform. Both are right.
One governed platform, in and out
Data flows in through monitored pipelines, gets modeled and defined once, and comes out as dashboards and AI answers that agree with each other. Snowflake is the core; our job is everything that makes the core worth having.
Diagram of a Snowflake-centered data platform: Airbyte pipelines and dbt models feed into Snowflake, which provides storage, compute, governance, semantic views, and Cortex AI with Claude. Outputs flow to BI tools including Power BI, Tableau, Looker, and Sigma, and to governed AI agents and applications. DSC adds architecture, migration, cost control, and semantics and AI enablement around the platform.
What we build on Snowflake
From first implementation to a governed, AI-ready platform your whole organization reports from.
- Snowflake implementation and platform architecture
- Migration onto Snowflake from legacy warehouses, with parallel-run validation
- Warehouse right-sizing and performance tuning
- Cost monitoring and optimization across warehouses and query patterns
- Governance: RBAC, row access policies, masking, and Data Metric Functions
- Semantic views and AI readiness, built domain by domain
- Cortex AI enablement: Analyst, Search, Agents, and AISQL with Claude
- Team enablement and ongoing platform operations
Outcomes
to stand up a Snowflake-based analytics foundation, depending on scope
And once you’re live, we keep the bill honest. Rightsizing over-provisioned warehouses and tightening auto-suspend limits routinely surfaces 15 to 30 percent in immediate monthly savings.
Frequently asked questions
What does Snowflake Select Partner status mean for us?
It means our implementation work is vetted by Snowflake and we have a direct line into their partner resources and roadmap. Practically, you get platform expertise and current best practices without vendor-scale consulting rates.
Can you reduce our Snowflake bill?
Usually, yes. Rightsizing over-provisioned warehouses, tightening auto-suspend limits, and fixing expensive query patterns are the common wins. A Medium warehouse running unnecessarily 24/7 costs roughly $4,000 a month on its own, and that kind of waste is usually straightforward to find and fix once someone is looking for it.
We’re not on Snowflake yet. Should we move?
It depends on your sources, workloads, and team, and we’ll give you a straight recommendation either way. If the answer is yes, we migrate with a parallel run and automated parity validation, so cutover is a scheduled event rather than a risk.
Can we run AI on our data without it leaving Snowflake?
Yes. Snowflake Cortex AI runs models, including Anthropic’s Claude, inside the platform’s security perimeter. Your existing role-based access, row policies, and masking apply to AI-generated queries exactly as they do to human ones.
Where this connects
Get more out of Snowflake
Whether you’re evaluating, migrating, or already deep in and watching costs climb, we’ll give you a straight answer on where you stand.
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