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In 2020, Snowflake announced a new global competition to recognize the work of early-stage startups building their apps — and their businesses — on Snowflake, offering up to $250,000 in investment as the top prize. Four years later, the Snowflake Startup Challenge has grown into a premiere showcase for emerging startups, garnering interest from companies in over 100 countries and offering a prize package featuring a portion of up to $1 million in potential investment opportunities and exclusive mentorship and marketing opportunities from NYSE.

This year’s entries presented an impressively diverse set of use cases. The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare.

Just as varied was the list of Snowflake tech that early-stage startups are using to drive their innovative entries. Snowflake Native Apps (generally available on AWS and Azure, private preview on GCP) and Snowpark Container Services (currently in public preview) were exceptionally popular, which speaks to their flexibility, ease of use and business value. In fact, 8 of the 10 startups in our semi-finalist list plan to use one or both of these technologies in their offerings.

We saw a lot of interesting AI/ML integrations and capabilities plus the use of Dynamic Tables (currently in public preview), UDFs and stored procedures, Streamlit, and Streamlit in Snowflake. Many entries also used Snowpark, taking advantage of the ability to work in the code they prefer to develop data pipelines, ML models and apps, then execute in Snowflake.

Our sincere thanks go out to everyone who participated in this year’s competition. We recognize the amount of work involved in your entries, and we appreciate every submission.

Let’s meet the 10 companies competing for the 2024 Snowflake Startup Challenge crown!


BigGeo accelerates geospatial data processing by optimizing performance and eliminating challenges typically associated with big data. Built atop BigGeo’s proprietary Volumetric and Surface-Level Discrete Global Grid System (DGGS), which manages surface-level, subsurface and aerial data, BigGeo Search allows you to perform geospatial queries against large geospatial data sets and high speeds. Capable of a headless deployment into Snowpark Container Services, BigGeo can be used to speed up queries of data stored in Snowflake, gather those insights into a dashboard, visualize them on a map, and more.


Implentio is a centralized tool that helps ecommerce ops and finance teams efficiently and cost-effectively manage fulfillment and logistics spending. The solution ingests, transforms and centralizes large volumes of operations data from disparate systems and applies AI and ML to deliver advanced optimizations, insights and analyses that help teams improve invoice reconciliation and catch 3PL/freight billing errors.


Focusing on food safety and quality, Innova-Q’s Quality Performance Forecast Application delivers near real-time insights into product and manufacturing process performance so companies can assess and address product risks before they affect public safety, operational effectiveness or direct costs. The Innova-Q dashboard provides access to product safety and quality performance data, historical risk data, and analysis results for proactive risk management.

Leap Metrics

Leap Metrics is a SaaS company that seeks to improve health outcomes for populations with chronic conditions while reducing the cost of care. Their analytics-first approach to healthcare leverages AI-powered insights and workflows through natively integrated data management, analytics and care management solutions. Leap Metrics’ Sevida platform unifies actionable analytics and AI with intelligent workflows tailored for care teams for an intuitive experience.


Quilr’s adaptive protection platform uses AI and the principle of human-centric security to reduce incidents caused by human errors, unintentional insiders and social engineering. It provides proactive assistance to employees before they perform an insecure action, without disrupting business workflow. Quilr also gives organizations visibility into their Human Risk Posture to better understand what risky behaviors their users are performing, and where they have process or control gaps that could result in breaches.

Scientific Financial Systems

Beating the market is the driving force for investment management firms — but beating the market is not easy. SFS’s Quotient provides a unique set of analytics tools based on data science and ML best practices that rapidly analyzes large amounts of data and enables accurate data calculations at scale, with full transparency into calculation details. Quotient automates data management, time-series operations and production so investment firms can focus on idea generation and building proprietary alpha models to identify market insights and investment opportunities. by Extropy 360

Pricing and analytics for chain restaurants is the primary focus of, a decision intelligence solution that combines ML models for price optimization and risk simulation with geospatial expertise. Restaurants can use SignalFlare to refine and analyze customer and location data so they can better capture price opportunities and drive customer visits.


Stellar is designed to make generative AI easy for Snowflake customers. It deploys gen AI components as containers on Snowpark Container Services, close to the customer’s data. Stellar Launchpad gives customers a conversational way to analyze and synthesize structured and unstructured data to power AI initiatives, making it possible to deploy multiple gen AI apps and virtual assistants to meet the demand for AI-driven business outcomes.

Titan Systems

Titan helps enterprises to manage, monitor and scale secure access to data in Snowflake with an infrastructure-as-code approach. Titan Core analyzes each change to your Snowflake account and evaluates them against a set of security policies, then rejects changes that are out of compliance to help catch data leaks before they happen.


Vector is a relationship intelligence platform that alerts sellers when they can break through the noise by detecting existing relationships between target accounts and happy customers, execs and investors. Vector can infer who knows whom and their connections by analyzing terabytes of contact, business, experience and IP data to determine digital fingerprints, attributes and shared experiences.

What’s next: Preparing the perfect pitch

In Round 2, each of these semi-finalists will create an investor pitch video, and their leadership team will be interviewed by the judges to discuss the company’s entry, the product and business strategy, and what the company would do with an investment should it win the 2024 Snowflake Startup Challenge.

Based on this information, the judges will select three finalists, to be announced in May. Those three companies will present to our esteemed judging panel — Benoit Dageville, Snowflake Co-Founder and President of Product; Denise Persson, Snowflake CMO; Lynn Martin, NYSE Group President; and Brad Gerstner, Altimeter Founder and CEO — during the Startup Challenge Finale at Dev Day in San Francisco on June 6. The judges will ask questions and deliberate live before naming the 2024 Grand Prize winner.

Register for Dev Day now to see the live finale and experience all of the developer-centric demos and sessions, discussions, expert Q&As and hands-on labs designed to set you up for AI/ML and app dev success.

Congratulations to all of the semi-finalists, and best of luck in the next round!

(This blog was originally posted on