How a fast-growing AI startup tamed spiralling Snowflake costs by 60%

SELECT provided immediate cost visibility with setup taking under one hour. The platform's Insights feature identified oversized warehouses and inefficient dbt models, while Automated Savings delivered quick wins from day one. SELECT's comprehensive cost breakdown enabled targeted optimization across their complex data infrastructure.

Synthesia operates a modern data stack with Snowflake as their central data warehouse, supporting over 300 total users. The platform serves 80 direct Snowflake users plus 250+ additional users through Omni for analytics and dashboards. Their data infrastructure follows a layered Kimball approach using dbt for transformations, Fivetran for ingestion, and Segment for event data. As a fast-growing AI company, Synthesia's Snowflake spending increased dramatically - growing 10X over two years as they scaled their platform and user base. The situation became critical when they realized their annual credit purchase would run out halfway through their contract, forcing immediate action on cost optimization.

Before SELECT, Synthesia relied primarily on Snowflake's built-in cost management interface, which proved inadequate for their complex infrastructure needs. The primary challenge was having no visibility over usage and workloads running on the platform. Snowflake's default cost management UI was very basic and wasn't cutting it for granular analysis. The challenge was compounded by the fact that non-technical team members had initially managed their Snowflake setup, with their original admin being a VP of Product. This meant the team lacked the technical foundation needed for sophisticated cost monitoring and optimization.

With costs spiralling and credits running out faster than expected, Synthesia needed immediate visibility into their Snowflake spending patterns. The adoption process was remarkably fast. While IT approvals took about a week, the actual SELECT setup took under one hour once permissions were in place. The team immediately activated SELECT's automated savings functionality, providing instant cost reduction benefits from day one.

Within the first month, SELECT enabled Synthesia to identify and address their primary cost drivers, resulting in dramatic savings. After enabling SELECT's Automated Savings feature, Synthesia shifted towards targeted interventions identified through SELECT's visibility and insights features. SELECT immediately highlighted specific areas for improvement, including dbt models that needed incrementalization and warehouses that were significantly oversized for their workloads. One major discovery was warehouses running three sizes larger than necessary, with SELECT's utilization metrics providing the confidence needed to right-size them immediately. The team also identified inefficient Census jobs syncing data to Salesforce that could be refactored or turned off entirely after consulting with business stakeholders.

SELECT transformed Synthesia's cost management from reactive firefighting to proactive monitoring. A routine was established of checking three to four customized saved views every Monday morning. Weekly monitoring includes warehouse costs at weekly and monthly horizons, long running queries customized for their specific use cases, unused assets, and monitoring recently introduced workloads. This streamlined approach takes just minutes but provides comprehensive visibility into their entire Snowflake environment, enabling early detection of cost spikes or new inefficient workloads. Beyond cost savings, the optimizations also delivered performance improvements on their dbt pipelines, creating additional value from their SELECT investment.

Synthesia plans to leverage SELECT as their central hub for all Snowflake cost reporting and analysis. The team is exploring using dbt meta keys from SELECT's dbt integration feature to allocate spending by department, enabling more granular cost attribution across their organization. As a cost-conscious company, this capability will be essential for maintaining their disciplined approach to spending as they continue scaling their AI platform. SELECT's upcoming Omni integration will provide additional visibility into dashboard costs and lineage, while partition monitors will enable granular cost anomaly detection at the dbt model level.