Project Snowflake Kemi
About the project
Project Snowflake Kemi is a cybersecurity analytics prototype that uses Snowflake to store and analyze structured security events. The project combines Python, FastAPI, SQL, synthetic security datasets, and a dashboard-oriented API. Its Snowflake database contains six verified sample security events, with SQL queries that analyze event severity. The application currently supports demonstration mode, while live Snowflake API authentication and Cortex AI integration are planned enhancements.
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**Project Snowflake Kemi — AI-Ready Cybersecurity Intelligence** Project Snowflake Kemi is a cybersecurity analytics prototype designed to demonstrate how Snowflake can support intelligent security monitoring and threat prioritization. We created a Snowflake database containing structured security events and validated SQL analytics that categorize activity by severity. Our Python and FastAPI application provides a publicly deployed dashboard, event summaries, and an interactive analyst interface using synthetic demonstration data. The architecture includes a Snowflake SQL API adapter for future live database connectivity and is designed to support Snowflake Cortex for LLM-powered security analysis. Our goal is to help security teams turn event data into actionable intelligence through a scalable Snowflake-based architecture.