Passerelle’s Data Rocket Banking Assistant is a flat-fee enterprise AI solution for banks and credit unions. Built on the Snowflake Data Cloud, it accelerates adoption of Snowflake Cortex with pre-engineered data models, curated YML files, and packaged use cases designed for financial services.
Instead of spending months designing models, prompts, and security frameworks, your teams can start applying AI to high-impact business questions immediately. The Banking Assistant enables faster time to value, predictable delivery, and governed, production-ready solutions that are aligned with industry best practices.
Financial institutions face growing pressure to deliver AI-driven insights across operations, customer experience, and compliance. But building from scratch can delay adoption and introduce risk. The Banking Assistant solves this by delivering:
Every Banking Assistant engagement follows a structured methodology designed to deliver quick wins and long-term scalability:
“Start now. You have to build the foundation. You have to keep progressing. There are great tools out there that can make you the master of your destiny. Don’t want around to see what somebody else is doing - you will miss out on opportunities.” Josh Nash, SVP and Director of IT, Camden National Bank
Empower business leaders with on-demand access to customer, account, and operations data. Move beyond static reports with pre-engineered prompts and data models that deliver daily management insights.
Use Cortex to query loan applications, PDFs, scanned documents, and images. Extract and analyze customer and applicant data that previously sat unused.
Automate data collection, summarization, and reporting to support financial, regulatory, and compliance audits. Reduce manual effort while improving accuracy and preparedness.
Measure customer sentiment in service interactions and analyze key trends—such as deposit balances or loan origination volumes—over time with packaged YML models.
Safeguard data with native security features that control access with data at rest.
A: This solution is not focused on conversational interfaces. It accelerates Snowflake Cortex adoption with prebuilt data models, YML files, and banking-specific use cases that enable faster deployment and measurable ROI.
A: Both structured (transactions, accounts, customer profiles) and unstructured (PDFs, documents, images) banking data.
A: With pre-engineered assets, many organizations see value in weeks rather than months.
A: Yes. The Banking Assistant leverages Snowflake’s native governance and security controls, ensuring compliance with regulatory and data privacy standards.
