How Seemore Data Acted as a “Team Multiplier” for PayChex to Reduce Snowflake Costs by 28%

Seemore Data transformed PayChex’s Snowflake operations by acting as a “team multiplier,” enabling a five-person skeleton crew to deliver the output of a thirty-person organization. Facing a 50% surge in monthly compute costs, the team leveraged Seemore’s automation capabilities to slash spend by 28%.

Beyond immediate savings, the platform secured $100,000 in rollover credits and provided the quantifiable evidence needed to curb developer inefficiencies.

By democratizing technical insights, Seemore bridged the headcount gap, allowing a lean team to achieve enterprise-scale optimization with zero additional engineering overhead.

Seemore Data delivered instant financial impact by identifying immediate wins that required zero engineering overhead. Within the first month, the platform helped reduce monthly compute expenditures from peak levels by 28%. 

These savings were primarily achieved through automated warehouse timeouts and SmartPulse scheduling. 

By the end of their Snowflake contract, the team realized $100,000 in rollover costs—credits that would have otherwise been wasted on inefficient compute. 

This quantification allowed the technical team to present a clear ROI to the finance department.

For a team of five managing 17,000 daily jobs, manual optimization was impossible. Seemore Data acted as a “team multiplier,” automating the research and identification of anomalies. Instead of engineers spending hours auditing logs, the platform pushed actionable alerts directly to them. 

This leverage allowed the skeleton crew to operate at a level their internal counterparts estimated would typically require 30 people within their corporate bureaucracy. 

The platform essentially filled the headcount gap created by reorganization, allowing the team to maintain high output without adding staff.

One of the most significant strategic impacts was the ability to hold internal developers accountable with hard data. 

With Seemore’s query history and plan analysis, the data engineering team could move from “guessing” to providing “quantifiable evidence.” 

This visibility allowed them to challenge users who unnecessarily scaled warehouses to 3XL, proving that the increased size did not improve duration but significantly increased costs.

Seemore’s intuitive UI lowered the technical barrier for team members with backgrounds outside of core engineering administration. Members focused on governance could now understand complex performance issues like spillage or queuing without being deep SQL experts. 

By providing clear explanations for why a query was failing or costing too much, Seemore enabled the entire team to contribute to optimization efforts.

Seemore Data served as a vital communication bridge between the data engineering team and the executive committee. 

By translating technical metrics into “dollars and time,” the platform allowed the team to justify its tech stack and its existence to finance stakeholders. 

When the budget was questioned, the team could show exactly how much they were saving through specific automations. This transparency moved the team from being viewed as a “cost center” to a strategic, highly efficient unit that proactively protects the company’s Snowflake investment.