RavenPack Accelerates Financial Insights and AI Innovation at Global Scale

The right data at the right moment lets investment professionals act decisively, uncover opportunities and protect their assets. Yet accessing these timely, high-quality insights is often complex and challenging. 

RavenPack’s mission is to remove technical barriers so financial professionals can access the insights they need, precisely when they need them. For more than 20 years, RavenPack has transformed unstructured financial data into structured, actionable insights, empowering leading hedge funds, banks, and asset managers worldwide to make informed investment decisions. With the recent launch of bigdata.com, RavenPack’s advanced agentic AI platform, finance teams can now build their own AI applications on top of a trusted financial data infrastructure, gaining even more powerful ways to research and analyze the markets they operate in.

Whether it’s powering a new paradigm in financial research or delivering mission-critical data to clients, RavenPack needed a data platform that could deliver secure, rapid data sharing — without extensive egress costs. To meet these demands, RavenPack chose a platform that could deliver secure, rapid data sharing at scale — Snowflake’s AI Data Cloud on AWS.

When your business deals in data, collecting and processing intelligence is just half the battle. You also have to find a way to quickly and securely send data to customers. It was a challenge for RavenPack, one that Roberto Martin, the company’s database manager, felt keenly. 

“Whether it’s hedge funds, banks or asset managers, our customers all place a great deal of importance on speed and data safety,” Roberto Martin says. “Streamlining the way customers access our data is critical to client satisfaction and enhancing data usability.” 

With a repository consisting of multiple petabytes of data, RavenPack was quickly finding that traditional FTP and ETL processes were leading to extended loading times that weren’t keeping up with customer demands. Plus, teams were operating in silos across different regions and cloud platforms, making data sharing difficult, time-consuming and costly. 

As it began looking internally, it also found its legacy data platform was limiting cross-functional collaboration within the organization and slowing down efforts to develop AI-driven insights and products. 

Roberto Martin and his team continued looking for a solution and eventually found it close to home. “When we met with customers, they told us they were using the AI Data Cloud. It quickly became clear that Snowflake was becoming a preferred channel for data sharing. So we saw an opportunity to meet our clients where they are — while improving scalability and simplifying integration.”

Ravenpack relies on Snowflake to power a centralized data repository that drives both internal and external data sharing, as well as data product delivery. The AI Data Cloud supplies data to bigdata.com, with AI agents pulling from a trusted platform to deliver superior insights to customers based on a wide range of premium datasets. 

With a fast, reliable way to deliver data to its customers, RavenPack has been able to quickly build new data products, leading to new revenue streams. One is called Annotations: a collection of large training datasets RavenPack offers through Snowflake for customers that want to train their own large language models. The other is a large dataset on job offerings, including insights into roles across different companies and the people holding them. 

As an organization that primarily uses cloud solutions and infrastructure from AWS, RavenPack was able to benefit from Snowflake’s seamless integration with AWS tools. For example, bigdata.com financial research agents are largely powered by AWS Bedrock, but can easily draw data from Snowflake to deliver the most useful insights to RavenPack’s customers.

RavenPack can now share data faster than ever before, and collaboration — internal and with customers — has soared. 

“In the financial world, every second counts,” Roberto Martin explains. “For customers, getting data even seconds earlier could lead to millions in extra revenue or profits. Just recently, I had a call with a new client that needed insights in near real time. And thanks to Snowflake, I could reassure them that this was possible.”

As soon as new data is processed, RavenPack’s clients can access it instantly — either directly or through bigdata.com’s financial AI agents. This keeps the data fresh and highly useful, while making it easier and faster for clients to work with. The result is a smoother, more satisfying experience that accelerates time to value.

Plus, with Snowflake zero-ETL data sharing, Ravenpack can create more efficient data sharing pipelines. Now that RavenPack has moved away from complex FTP processes and API management, it’s eliminated the need for clients to download large files manually while enhancing security.

“The ability to share data instantly and securely has allowed us to grow our business by easily sharing data across teams and with our clients,” shares Roberto Martin. “It’s enabled us to move from a fragmented, labor-intensive data delivery model to a streamlined, secure, and highly efficient data sharing ecosystem. This has not only improved our internal operations, but also significantly enhanced the value we provide to our clients. Snowflake’s platform has made this possible.”

As a leader in AI-powered financial insights for Wall Street, RavenPack sends vast volumes of data to its customers across different global regions and clouds. As a result, egress costs were top of mind for Roberto Martin and his engineers. With Snowflake Egress Cost Optimizer, which intelligently routes data, they could be confident that fast, secure data sharing was still seamless for global teams — and wasn’t going to lead to spiralling costs.

A key optimization was avoiding duplicate data across regions. RavenPack shares data to 15 regions, with plans to expand to new parts of the world over time. This means Ravenpack’s egress costs will continue to rise, but with Egress Cost Optimizer, the financial insights provider can maintain control of its expenses. 

“With Snowflake, we can have one source of data being used across all 15 regions where Ravenpack customers are active,” Roberto Martin explains. “Already, that helps us reduce our costs 14-fold. It also means we can optimize egress costs for one region, and see the benefits worldwide. It’s led to huge cost savings for us.”

For RavenPack, removing technical barriers means they can bring in an ever-wider range of data sources — from flight details or shipment tracking to geographic insights on earthquakes and other disruptions, and more.

Looking ahead, RavenPack is confident in its ability to scale and innovate. As Roberto explains, “Our focus is on delivering the most valuable insights to our clients. By streamlining our data infrastructure and expanding the types of information we can offer, we can continue to push the boundaries of financial intelligence.”