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Introducing the 10 Snowflake Startup Challenge Semi-Finalists for 2022

ML, AI, and decision intelligence. Predictive analytics, carbon reduction, and crypto blockchains. These exciting initiatives are a small sampling of the innovative work being done by this year’s Snowflake Startup Challenge contestants. 

The 2022 Startup Challenge drew hundreds of entries from early-stage startups, including many high-quality submissions and unique approaches to building products in the Data Cloud. With so many strong entries, the judges had to make some difficult decisions to select the top 10. Our sincere thanks go out to everyone who participated in this year’s competition—we recognize the amount of effort involved in crafting your entries, and we appreciate every submission. 

The 10 semi-finalists represent not just technical innovation, but also the global nature of our competition: half of the companies come from countries outside of the U.S. The founders bring diverse viewpoints and experiences to their companies, along with a passion for data.

That passion—along with business potential, strength of leadership team, and how the product leverages Snowflake—will be a key factor in determining the winner of the Snowflake Startup Challenge. The grand prize winner may receive up to $500,000 and the two runners-up may receive up to $250,000 each in investments from Snowflake Ventures, along with co-marketing opportunities and valuable VC exposure. 

Now, without further ado, here are the 10 semi-finalists in alphabetical order:

Adaptive Pulse

Adaptive Pulse helps B2B SaaS companies understand their customers’ behaviors to help reduce churn and increase net revenue retention. By analyzing historical and real-time customer data, including unstructured data from support tickets, email, phone transcripts, and social media, Adaptive Pulse produces predictions and recommendations on which customers need attention and how retention teams can be most effective. 

Datacoves

Datacoves is a turnkey analytics workbench that helps companies implement the components of the modern data stack in minutes with proven software engineering best practices, and by removing complexity without locking them into proprietary solutions.

Houseware

Houseware is a revenue analytics workbench that enables anyone to build internal data apps on the Snowflake Data Cloud. It connects to more than 150 data sources, abstracts schemas, columns and rows into higher-level metrics, empowering the creation of visualizations, rules-based actionable signals, and much more without coding.

Hyper

Hyper is a no-code decision intelligence platform that puts data science and AI in the hands of nontechnical decision makers. It helps retailers and brands optimize decisions about what products to offer, how to price them, how to market them in personalized ways, and how to make them available when customers want them without relying on scarce data science and AI talent.

Kolena

Kolena is a machine learning (ML) testing and evaluation platform that enables data science teams to implement high-resolution unit and functional tests for their models. Using Kolena, customers surface hidden behaviors and failure modes, iterate faster, and automate testing workflows to ship models with confidence.

Modelbit

Modelbit enables data scientists to train and deploy ML models in the cloud without leaving their Jupyter notebooks. It connects their notebooks, where they do their model development work, to the modern cloud data stack.

Ocula Technologies

Ocula seeks to democratize AI and provide actionable insights where they matter most for consumer-facing businesses. Its first modules help clients transform their ecommerce conversion, product pricing, and customer insights. Set up is rapid, required IT support is minimal, and business users enjoy clear, prioritized recommendations to drive online growth.

Radiant Labs

Radiant Labs offers tools, data, and insights that drive carbon-reduction solutions for cities, states, and utilities. Its tools help city planners, policymakers, and property owners make building improvements by creating individual models for millions of buildings rather than relying on top-down modeling with average energy usage data.

Sled 

Built for the Snowflake ecosystem, Sled makes it easy to find, understand, and trust analytics assets. It includes a data catalog to preserve knowledge and discover data, a metric store to have consistent metrics across reports, and data observability tools to automatically detect significant changes in the data landscape. 

Sonarverse

Sonarverse is a web3 analytics platform providing data and business intelligence for institutions, retail investors, and decentralized applications (dApps) across major crypto blockchains and protocols. It offers insights on smart contracts in addition to transaction data via a dashboard and Snowflake Data Marketplace.

Moving On: Round 2 and the Finale

In Round 2 of the Snowflake Startup Challenge, each semi-finalist will submit an investor pitch video and have an interview with the judges to discuss its entry, the product and business strategy, its leadership team, and how the company would use an investment. Based on these interviews, the judges will select three finalists, to be announced in late May.

The three finalists will take to the stage and pitch their startups to our esteemed panel of judges in the Startup Challenge Finale at Snowflake Summit in June. The judges will deliberate and select the grand prize winner live, in front of the Summit audience, and we hope you’ll join us to see the Finale in person. In addition, attend our Founders’ Series webinars to hear from other startup founders building in the Data Cloud.

Congratulations to the 2022 Snowflake Startup Challenge semi-finalists. We look forward to the next rounds of competition and seeing who will take home the grand prize!

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