The stage is set for the Finale at Snowflake Summit
We started with over 250 contenders; our judges narrowed that down to 10, and now just 3 remain. We are pleased to announce that Houseware, HyperFinity, and Modelbit will advance to the Finale of the Snowflake Startup Challenge and compete for the opportunity to receive a share of up to $1 million in investments from Snowflake Ventures!
Congratulations to the finalists and big thanks to the 10 semi-finalists (announced previously) for the quality of their entries and their presentations to the judges during the previous round of competition.
Let’s get to know the 2022 finalists!
HyperFinity
“We’re delighted to reach the finale of this prestigious competition with so many innovative early-stage companies entering,” said Peter Denby, Chief Commercial Officer of UK-based HyperFinity. “To reach the final three is a huge endorsement of the product we’ve built and the opportunity for retailers and consumer packaged goods companies to transform their commercial decision-making.”
HyperFinity has a unique proposition within the decision intelligence market: a completely no-code solution that puts data science and AI in the hands of the people responsible for making business decisions. HyperFinity leverages Snowpark to enhance its lightweight serverless architecture, which enables faster deployment of new features and a quicker time to release. This allows the creation of extremely scalable, compute-intensive processes in a much more cost-effective manner.
“Snowpark in particular has excited us from day one as we explored scalable machine learning solutions,” said Denby. “We’ve also used data sharing within Snowflake to great effect, giving us confidence in the security and speed of exchanging information with our clients.”
Studio Retail, a multi-channel retailer, is already working with HyperFinity to make intelligent marketing, media, assortment, and pricing decisions that deliver great experiences for customers and commercial outcomes for Studio. To date, HyperFinity has supported Studio in making more effective use of promotions and incentives, customer-centric category merchandising, and personalized digital marketing. By combining HyperFinity’s leading-edge technology and key Studio data sets, Studio has significantly improved the level of customer insight and commercial decision-making available at the touch of a button.
Modelbit
For Modelbit, the move to the cloud represents the largest data industry shift in a generation—and data scientists need to join that movement. With that in mind, Modelbit allows data scientists to connect to the Data Cloud by running their machine learning (ML) workloads directly in their Snowflake instances.
“The opportunity to pitch at Snowflake Summit as a Startup Challenge Finalist brings us another opportunity to show what Modelbit can do for data scientists who are building on Snowflake,” said Harry Glaser, co-founder and CEO of Modelbit.
Modelbit leverages Snowpark for Python (currently in private preview) to run ML models in Snowflake, allowing data scientists to deploy their models straight from their notebook. ML workloads can run adjacent to their training and live scoring data, unlocking scale and efficiency.
Bambee, which offers outsourced HR management solutions, is taking advantage of the opportunities afforded by Modelbit. It is using Modelbit to deploy an ML model that can score inbound sales leads in Snowflake as well as from the Bambee website. After training the model in a Jupyter notebook, Bambee’s data team called “modelbit.deploy” to deploy the model simultaneously to Bambee’s Snowflake instance and a REST API.
Now, new leads are scored in batch in Snowflake every hour—a dramatic improvement. Meanwhile, with the REST API, Bambee can score the same leads on the website in real time as they come in. This allows Bambee to deliver a custom experience to each new prospect depending on their lead score.
Houseware
Houseware’s goal is to build a scalable, flexible, and collaborative data app ecosystem that extends data access beyond data teams. It empowers knowledge workers to build data apps on top of their own Snowflake instance or a Houseware-managed cloud data warehouse without writing code.
“The Snowflake Startup Challenge for us started as a natural foray to build the neatest product integration on the Data Cloud,” said Divyansh Saini, co-founder of Houseware. “However, as a finalist, it has turned out to be much more than just access to the Snowflake team, and it is refreshing to now paint a ‘better together’ story with Snowflake and Houseware.”
Houseware uses the Snowpark API and UDFs, enabling knowledge workers to run pre-defined ML models for forecasting, churn, and other complex predictive analytics scenarios with just a few clicks.
That agility attracted Quizizz to the Houseware app ecosystem. An engagement-driven learning platform used by over 65 million students and teachers, Quizizz found it difficult to activate data across finance, sales, and customer success departments. Despite a lot of heavy lifting by the Quizizz data team, metrics varied because they were defined differently in the departments’ function-specific tools.
The Houseware solution helps the Quizizz team address two problems: surfacing reliable metrics and creating a culture of experimentation across the go-to-market teams. Quizizz can now drive user engagement with product action triggers and keep tabs on customer health. Plus, metrics are reliable and consumable across tools and functions, instead of just living in a dashboard.
On to Las Vegas and the Finale at Snowflake Summit
These three startups now enter the final phase of the Startup Challenge: making their pitch to a stellar judging panel, live at Snowflake Summit in Las Vegas. They will field questions from judges Benoit Dageville, co-founder of Snowflake; Denise Persson, CMO of Snowflake; Carl Eschenbach, partner with Sequoia Capital; and Jayshree Ullal, CEO of Arista Networks—who will then confer before announcing the contest winner on stage.
Having received hundreds of quality entries from organizations around the world, the Snowflake Startup Challenge, only in its second year, has already grown into a premier global competition for startups. We’re excited to see what’s next, both from our three finalists and from the broader startup community. We hope to see you at the Finale on June 16, and invite you to join our Founder’s Series webinars to hear from other startups building in the Data Cloud.
Note: Snowpark API is available on Scala, currently in public preview for Java, and currently in private preview for Python. Java UDFs are generally available; Python UDFs are currently in private preview.
