How Verbit Slashed Data Costs by 70% While Gaining Total Visibility with Seemore
Verbit, a leading AI transcription and captioning company and global provider of AI verbal intelligence, scaled rapidly by acquiring 7 companies in a short span. Each had unique data architectures, repositories, and processes—and many of them had previously made their own acquisitions of companies with unique data stacks.
To unite these disparate systems, Verbit’s data team led a massive migration to Snowflake, ensuring all data would effectively “speak one language.” But even with Snowflake at the core, merging so many infrastructures created an intricate data landscape and a mounting need for cost efficiency and streamlined data operations.
70% yearly savings
through warehouse config tuning
10% saved
by adjusting one query’s schedule
30 min
data stack integrations
Challenges solved for Verbit
AI-Based Transcription & Captioning
United States & Israel
500 employees
7 companies in 2 years
A single data team responsible for maintaining data infrastructure for the growing company
October 2024
Visibility Across a Complex Data System
With multiple newly integrated infrastructures, the data team struggled to see how everything interconnected, understand ownership, and track changes that could impact downstream dashboards and processes.
Optimization of a Modern Data Stack
Adopting Snowflake, Rivery, and Tableau at scale introduced cost, performance, and governance challenges—especially under tight timelines as the organization continued expanding.
With Seemore, Verbit identified opportunities to merge and optimize warehouse sizes and configurations based on current workloads, significantly reducing unnecessary compute usage and cutting overhead dramatically.
As an example, a single information security query was found to be running five times more often than intended; fixing that one issue alone saved Verbit 10% of our yearly spend. Overall, Seemore achieved a 70% reduction in total warehouse costs.
For Verbit’s data team, Seemore’s greatest value goes beyond saving money—it’s about total transparency across the data lifecycle. By offering a unique Deep Lineage, Seemore allows the team to spot changes before they cause widespread issues.
Visibility through lineage isn’t just a technical benefit; it empowers executives who need a high-level view of how new acquisitions or team expansions affect data flows.
Buoyed by significant warehouse savings, Verbit is now ready to broaden its use of Seemore. The next phase is to optimize the entire data stack—including ingestion and transformation processes—to achieve even greater efficiency and control. Verbit also plans to extend Seemore’s usage and benefits within and beyond the data team, involving other key stakeholders across the organization. This shared responsibility and attribution of ownership will enhance data cost governance and drive continuous improvements in performance and overall data efficiency.
Seemore case studies
Yearly savings
Saved from one query
Data stack integration
Ilanit Rapaport, Director of BI & Analysis
Cost reduction
Run-time reduction
Instantly saved
Hannan Kravitz, Data Engineering Team Leader
a year saved
warehouse cost cut
to save by BI DW downsizing
Dror Yosef, Chief Data Officer
Assaf Bazar, VP Architecture & Data
Seemore resources
