JB Kole

Blogposts written by JB

Turning a Complex Synthetic Data Workflow into a Simple Dialogue

November 17, 2025

Synthetic data workflows have traditionally required a mix of engineering effort, platform knowledge, and careful coordination across tools. You upload a dataset, write code to explore it, adjust preprocessing steps, configure a generator, train it, generate data, build a model, and eventually compare results. It is powerful, but rarely simple. This time, I tried something […]

Mock Data That Acts Like Reality

October 15, 2025

I wanted to generate realistic mock data: structured, relational, and coherent enough to actually build with. That’s where I started—not as someone at MOSTLY AI, but as someone in the shoes of a data scientist or engineer who just needs believable data to begin. Something that looks and behaves like production data, without exposing any […]

From Mock Data to Scalable Synthetic Datasets: Building a Healthcare Use Case with the Assistant

Creating realistic, relational healthcare datasets doesn’t need to be complicated. In this blog, I walk through how to use the Assistant from MOSTLY AI to simulate a multi-table Healthcare and Life Sciences (HLS) use case from scratch. The entire process flows through natural language, making it intuitive even for non-technical users. This workflow includes two […]

Proving the Power of Synthetic Data for Cybersecurity: MOSTLY AI x U.S. Department of Homeland Security

In partnership with the U.S. Department of Homeland Security (DHS), MOSTLY AI completed a multi-month proof of concept (PoC) focused on one of the most pressing challenges in cybersecurity: enabling advanced analytics and machine learning while maintaining strict data privacy and regulatory compliance. The core objective was to determine whether synthetic data could replace sensitive […]

Synthetic Data for Financial Services—Enabling AI While Protecting Privacy

February 27, 2025

The Challenge: Enabling AI Without Exposing Sensitive Financial Data Financial institutions rely on AI and analytics for fraud detection, risk modeling, and strategic decision-making. However, strict privacy regulations like GDPR and CCPA make it difficult to access and use financial data. To comply, teams often resort to:🚧 Manual data masking that distorts data quality.🚧 Complex […]

Accelerating Privacy-Preserving Synthetic Data in Databricks with the Open-Source Synthetic Data SDK

February 19, 2025

Access to high-quality data is essential for organizations to accelerate AI and analytics initiatives. However, privacy concerns, compliance constraints, and slow data access often stand in the way. Privacy-preserving synthetic data removes these roadblocks, providing on-demand, high-fidelity datasets without compromising sensitive information. Powered by MOSTLY AI, the Synthetic Data SDK enables you to generate synthetic […]

Accelerating Data Innovation with MOSTLY AI’s GenAI Synthetic Data Platform and Databricks

October 4, 2024

Introduction In today’s data-driven world, the ability to leverage high-quality, privacy-safe data is paramount. The MOSTLY AI Platform provides a suite of advanced data capabilities, including synthetic data generation and generating AI-driven insights. To streamline the integration of these capabilities within Databricks, we’ve developed a comprehensive Solution Accelerator. This blog post outlines the goals and […]

Data Democratization at Scale: Announcing the MOSTLY AI and Databricks Integration

Today we’re excited to announce the new MOSTLY AI and Databricks integration. The collaboration between MOSTLY AI and Databricks is not just a partnership; it's a leap forward in how businesses innovate with data. By seamlessly integrating MOSTLY AI’s GenAI synthetic data generation with Databricks’ Data Intelligence Platform, this alliance redefines the boundaries of data […]

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