A shared source of truth for data teams living in Snowflake. Automated financial and operational ERP insights. AI services for semantic processing of unstructured information.
What do these three things have in common? Each is the primary mission of a 2023 Snowflake Startup Challenge finalist!
We are pleased to announce that Honeydew, Maxa, and semantha.ai will advance to this year’s Snowflake Startup Challenge finale and face off for the opportunity to receive a share of up to $1 million in investment from Snowflake Ventures, plus exclusive mentorship and visibility opportunities from NYSE.
Many thanks to the other semi-finalists for their presentations during the second round of competition. We appreciate your effort and dedication.
Read on to learn more about the 2023 finalists, their solutions, and which judges they’d prefer to be stuck in an elevator with. And be sure to register for Snowflake Summit so you can attend the live finale!
“Getting to the finals is, for us, a recognition of how important the problem of shared truth is,” says David Krakov, Co-Founder and CEO at Israel-based Honeydew. “We are inspired by Snowflake, and we are really excited to be on the Finale stage.”
Honeydew aims to provide a shared source of truth for data teams who live in Snowflake. By building a collaborative semantic layer that sits between the data platform and data tools, Honeydew helps ensure that core business metrics like revenue, churn, or daily active users remain consistent. Data teams can organize analytics into manageable and reusable blocks of knowledge supporting every data flow; users can consume them via SQL, Tableau, Looker, Python, or dbt.
“Snowflake helps data teams consolidate their data,” says Baruch Oxman, Co-Founder and CTO at Honeydew. “We leverage Snowflake’s core compute and storage capabilities to make the single source of data into a single source of business logic.”
At-Bay, a leading cyber insurance company, aims to leverage Honeydew to do just that. With a single definition for customer journey KPIs, At-Bay can provide its business users with consistency and flexibility. For example, the At-Bay central data team controls how insurance policies are counted. Before Honeydew, they had to build that KPI for every context of every business domain, creating friction with users, potential data errors, and a development backlog. With Honeydew’s semantic layer, each data user will be able to freely leverage the KPI in the tools they are already using and within their business context.
Honeydew’s team is excited to present at the finale, and if they happen to get stuck in a Las Vegas hotel elevator with the four Startup Challenge judges, they won’t worry at all: “Brad’s piloting experience helps us keep a cool head. Benoit teams up with Lynn and they brush up their engineering skills to fix the elevator circuits. Denise organizes the rescue team with just the elevator speakerphone,” explains Liron Slonimsky-Shemy, Co-Founder and Growth at Honeydew. “After we all get out, we’re all friends and we can go out for drinks and a post-elevator pitch.”
Maxa’s goal is to automate financial and operations ERP insights extremely fast and with no special skills required. To make that happen, it leverages the breadth of the Snowflake platform to ingest billions of rows of data and transform it into a unified model, Python support via Snowpark to run model training and forecasting inside Snowflake, data sharing via Snowgrid to consume and share data with customers around the world, Streamlit to power the Operator UI and self-service experience, and more.
“Snowflake is in a class of its own, and therefore, so is the Startup Challenge,” says Alexis Steinman, Co-CEO and Co-Founder of Maxa. “We expect the Startup Challenge to create all sorts of opportunities and discussions that never would have occurred without it—we see it happening already!”
Maxa is currently deployed as a managed app with data sharing for customers on Snowflake, as well as a connected app that allows customers to store and process data in their own Snowflake environment. And the Maxa team is currently developing a Snowflake Native Application.
“We are in the process of transforming our application into a Snowflake Native App for the next phase of our growth,” says Steinman. “The Snowflake Native App Framework will offer us unique capabilities to run fully in a customer’s Snowflake environment while protecting our intellectual property, and we will use Snowflake Marketplace to list and monetize our app.” (Note: the Snowflake Native App Framework is currently in private preview.)
One of Maxa’s early customers is also lining up to be one of its first to migrate from using Maxa’s managed app to using their Snowflake Native App. AJW Group, through its division AJW Technique, provides aviation services including maintenance, repair, and overhaul for global airlines. AJW uses Maxa’s solution to automate data model transformation and to run powerful analytics. By leveraging automated pricing, sales, inventory, and procurement analytics, AJW teams can focus on winning business and improving efficiency instead of wrestling with system data.
Maxa is based in Canada and its founders are big fans of skiing, so if they’re going to be stranded somewhere with a Startup Challenge judge, it won’t be in an elevator. “How about being stuck on a broken ski lift?” suggests Raphael Steinman, Co-CEO and Co-Founder of Maxa. “With Benoit’s exceptional creativity, he could probably find ingenious ways to get us out!”
While the potential Snowflake Ventures investment is enticing, the team at semantha.ai is salivating at the thought of winning a mentorship from NYSE-listed companies.
“Honestly, we consider this the main prize of the Startup Challenge,” says Sven Koerner, Managing Director and Founder of semantha.ai, which is based in Germany. “Being able to connect to this network and ‘tap into’ their minds is a crazy benefit we’d want to make the most of.”
semantha uses a variety of Snowflake services—including Snowpark, Streamlit (for the UI), data sharing, UDFs, and the VARIANT data type—to offer AI services for semantic processing of unstructured data. The semantha semantic platform processes large numbers of documents to find relevant content, compare it to identify similarities and differences, extract and structure data points, and use those data points to draw logical conclusions. The goal, according to the semantha team, is “a world without information overload.”
Use cases for semantha cross all industries, ranging from contract analysis to specification processing and compliance management. For example, ESG initiatives often involve assessing and evaluating sustainability and social responsibility as well as multiple mandates and regulations. semantha can help analyze massive amounts of unstructured, potentially ESG-relevant information and make a significant contribution to the transparency necessary for these initiatives to succeed.
The semantha team is looking forward to competing at Snowflake Summit in Las Vegas and promises to “put on a show.” They are most excited to meet Denise and Benoit at the Startup Challenge finale—but Koerner feels that the NYSE Group’s president’s expertise would be most useful when stuck in an elevator. “Lynn Martin has the tech knowledge to get us out of the elevator while being able to lead the most insightful conversations to keep me calm,” Koerner explains.