From Manual Chaos to Automated Signal
How a $10B+ VC Fund Went from Spreadsheet Chaos to Automated Pipelines in 45 Days
About Venture Capital Fund
A global venture capital firm managing over $10B in assets needed to improve how it monitored fund performance. Key financial data lived in manual spreadsheets spread across Box, owned by different teams, with no centralized structure or automated flow.
Challenge
There was no internal analytics team—but there was urgency to deliver clean, reliable data to stakeholders. The goal: eliminate manual processes and build a system to ingest, transform, and secure sensitive financial data for reporting and analysis. Gun.io deployed a trial analytics pod—a data scientist paired with a data engineer—in under one week.
Solution
Gun.io automated and streamlined fund performance monitoring by replacing manual spreadsheet processes with reliable, scalable data pipelines.
The team used Airflow to build DAGs that ingest and orchestrate data from Box using the Box SDK, dbt to model data marts and implement custom monitors for anomaly detection and metric integrity, and Snowflake to manage access and security—including schema and role-based safeguards for sensitive financial data.
The team used Airflow to build DAGs that ingest and orchestrate data from Box using the Box SDK, dbt to model data marts and implement custom monitors for anomaly detection and metric integrity, and Snowflake to manage access and security—including schema and role-based safeguards for sensitive financial data.
Strategic Takeaway
Build Leverage Before Headcount
Manual work is error-prone. Hiring takes time. Gun.io's model delivers infrastructure-grade outcomes—with speed, security, and zero recruiting drag.
The result? A modular, trial-ready pod that builds trust fast, integrates cleanly into your systems, and scales when you're ready.
