A data analytics partner for FIs focused on growth

Helping you grow your bank or credit union with a data analytics program that’s both usable and profitable.

The partner credit unions and community banks trust to reach their objectives.

“Gemineye proves to be an invaluable partner, wholeheartedly dedicated to aiding us in realizing our data analytics objectives.”
– Clint Johnson, VP of Data & Analytics at P1FCU

“Gemineye distinguished themselves through a highly collaborative approach, demonstrating the mindset of a strategic partner rather than a traditional vendor.

– Sameer Barua, Director of Data Analytics at DFCU

“The true value of Gemineye is that y’all have lived up to the promise of being our analytics partner and not just another vendor.”
– Chris Clifford, Data Analyst at Mobility CU

Who is Gemineye?

Gemineye provides data analytics solutions to credit unions and community banks across the country. We believe that regardless of whether you’re a $200M credit union or a $25B bank, you should have access to a data solution that works the way you need it to.

Our signature solution, the Gemineye Data Lakehouse, is the leading industry choice for organizations looking for customization and ownership of their data journey hefty price tag or lengthy timeline. How? By using the same world-class tools that Fortune 50 companies enjoy – Databricks and PowerBI.

We believe the key to success in a data program comes from a partner relationship with our clients. Our personalized approach to each engagement and complimentary EaaS ensure that your specific needs and goals are captured for maximum results.

Our History

Continual growth called for a new brand, entering a fresh chapter of FI data solutions. We now support all major cores and 75+ integrations!

Our Values

You should own your data journey

Your data program shouldn’t be confined to a tiny dark can. We believe that credit unions and community banks deserve to own their data and their data journey. We believe that a practical and usable data program is the key to success. We believe that every financial institution – no matter their size – deserves access to the world-class technology Fortune 50 companies use.

At Gemineye, we take a different approach to data analytics, one that puts our clients back in the driver’s seat of their own data journey. Your data, your definitions, your decision.

A persistent data partner

Innovators at heart, our persistence in problem-solving has made us the clear choice for financial institutions who won’t settle for second best. We pride ourselves on our ability to brainstorm, research, and carve out solutions to tough problems.

The very best data team

The Gemineye team consists of data and technology experts with decades of credit union and banking experience, data warehousing design, SQL and ETL development, and API development.

Combined, we create a supergroup of skilled experts with modern sensibilities in the data space. Count on us to provide honest answers, recognize industry-centric trends, and act as a dependable partner in your journey.

News and Resources

Alison Stanback: Business Intelligence Analyst at Space Coast CU

In this edition of “A Day in the Life of a Data Analyst,” we feature Alison Stanback, Business Intelligence Analyst at $8B Space Coast CU, the third largest credit union in Florida. Alison’s straightforward and optimistic approach to data analytics is equally inspiring and hilarious. She had Alicia Disantis, Head of Marketing at Gemineye, in tears. We sat down to talk with Alison about her grassroots journey into data analytics, her daily routines, and her outlook on communicating with business units.

What a Data Lakehouse Actually Is

A data warehouse is a structured, modeled system designed specifically for analytics and reporting. It provides:

• Governed, consistent metrics
• Standardized business definitions
• Historical tracking and transformations

Choosing a true data warehouse matters because of the potential for:

• Inconsistent metrics
• Lack of trust in data
• Wasted effort and money
• Lost time
• Slower decision-making.

# Data Tool Categories and Examples
Table of types of data tools and their primary use.
| Tool Category | Primary Use | Why It’s Not a Warehouse |
|---------------|-------------|-------------------------|
| BI Tools      | Visualization | No data modeling or governance |
| Managed Analytics | Outsourced insights | No internal ownership of data |
| Data Lakes   | Storage | No standardized metrics |
| Reverse ETL  | Activation | Depends on warehouse |
| CDPs | Customer profiles | Limited scope |
| Data Augmentation | Data quality | No modeling or governance |
| Core Systems | Transactions | Not optimized for analytics |
| Marketing Platforms | Engagement | No unified data model |
| AI Platforms | Predictions | No metric definition |

This summary helps financial institutions differentiate between a true warehouse solution and tools that merely sit adjacent to it.

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