How Fireblocks Uses Snowflake Cortex AI to Handle 40-50% of Data Queries Autonomously
Fireblocks, the digital asset infrastructure powering $10 trillion in transactions across 550 million crypto wallets, deployed Snowflake’s AI Data Cloud to unify 15 data domains and build an AI agent called Fire Genie. The agent lets customers query their wallet and transaction data in natural language through a secure API, handling 40–50% of all data queries autonomously. The company saves the equivalent of two full-time analysts per month from AI-powered efficiencies across its data platform.
Impact
40-50%
Data queries handled autonomously by AI agent
2 FTEs
Analyst capacity saved per month
Challenge
With billions of rows across 15 data domains, queries were taking up to 20 minutes and cross-domain analysis was impossible. Customers and internal teams had no way to self-serve data insights without analyst involvement.
Solution
Snowflake AI Data Cloud on AWS unified all 15 data domains. The team then built Fire Genie, an AI agent using Snowflake Cortex Agents and semantic views that lets customers query their wallet and transaction data in natural language through a secure, role-based API.
Tools & Technologies
What Leaders Say
“Snowflake wasn’t a ‘nice to have’ for us. It was an absolute must so we could continue growing.”
Sign up to read complete case studies, access detailed metrics, and unlock all use cases.
Full Story
Fireblocks provides the infrastructure behind much of the digital asset economy — its platform secures and moves $10 trillion in transactions across 550 million crypto wallets for hundreds of institutions and fintechs. The scale of data that generates is enormous, and it was growing faster than Fireblocks’ infrastructure could keep pace.
Before Snowflake, even basic queries across billions of rows were taking up to 20 minutes. The company operated 15 separate data domains, each with its own data and semantic layer, making cross-domain analysis nearly impossible. Sales reps couldn’t get revenue insights while engineers were pulling on-chain data — the systems didn’t talk to each other.
Fireblocks built a new data platform on Snowflake, running on AWS. With all 15 domains flowing into the AI Data Cloud — from Salesforce analytics to Zendesk insights to on-chain transaction data — any team can now query across the full data estate. During a 45-day internal hackathon, the engineering team built Fire Genie: an AI agent using Snowflake Cortex Agents and semantic views that lets customers query only their own data in a secure environment through a natural language API.
The results shifted how the business operates. Fire Genie now handles 40–50% of all data queries autonomously, replacing what previously required direct analyst involvement. The AI-powered efficiencies across the platform save the equivalent of two full-time analysts per month, freeing the team to focus on higher-value work.
With row-level security and RBAC enforced at the Snowflake layer, Fireblocks is able to offer customers genuine self-service — without the risk of data leakage between accounts. The platform now scales with transaction growth rather than headcount.