Pacific Life Protects Its 150-Year Legacy with Snowflake CoCo

Every life insurance policy is a promise, sometimes made decades before it’s ever called upon. When a family files a claim or a customer plans for retirement, the answers sit in structured data going back generations. For a carrier with more than 150 years of history like Pacific Life, that depth is an asset. The opportunity was reaching it faster.

Pacific Life Insurance Company was running analytics on on-premises databases with a NetApp file structure, and a growing data set meant physically extending disk space. Training models on large historical data sets was slow. Taking months from start to finish, every project followed the same path: pull large data, run a principal component analysis, train on historical content and build a what-if dashboard.

Business teams in finance, sales and customer service also had to route every question through data engineering first. Those teams needed to understand data structures and object relationships before they could engage with the data at all. For a company planning its next 150 years, that pace was no longer sustainable.

Pacific Life Insurance Company turned to Snowflake to move off its on-premises infrastructure and modernize how it runs data and AI. The benefits of switching to Snowflake were clear from the start: reducing maintenance overhead and running large model workloads without the disk constraints of the old environment.

The team’s adoption path followed Snowflake’s fast-evolving AI capabilities, starting with Document AI before adopting Cortex Analyst and then Snowflake CoCo. With CoCo, Pacific Life rapidly changed model development. Instead of starting with a large data pull and a months-long training cycle, the team now describes what it’s trying to achieve and asks CoCo to help build the process. Projects that previously took months now take weeks.

Three use cases are now active. The finance team runs near real-time what-if scenarios daily through Streamlit in Snowflake dashboards. Sales receives AI-generated insights nightly, delivered directly to its CRM. The customer service team runs call analytics, using the results to continuously improve how it handles interactions.

Pacific Life Insurance Company is delivering analytics output in weeks without sacrificing the quality standards it has maintained for 150 years.

The biggest shift is happening inside the analytics organization itself. Analysts and developers who once had to route every data question through engineering now engage directly. The AI barriers are coming down. Teams that once thought these tools demanded deep technical expertise are realizing that their business context is the most valuable input. And the technical complexity now lives in the tools, so teams spend their time on the business instead of the infrastructure behind it.

Still in the early stages, the team is already shifting focus from automating existing steps to rethinking those processes entirely, starting with the business problem instead of the pipeline. For a company whose mission is keeping its promises across generations, that means moving faster while staying true to its time-honored standards.