The traditional five-year anniversary gift is wood. Since snowboards often have a wooden core, and because a snowboard is the traditional “trophy” for the Snowflake Startup Challenge, we’re going to go ahead and say that the snowboard trophy qualifies as a present for the fifth anniversary of our Startup Challenge. The only difference is that instead of receiving the gift, we’ll be giving it to one of the 10 semifinalists listed below!
With more than 1,000 submissions from over 100 countries, this year’s Startup Challenge applicant pool was an exciting mix of technical innovations. As you might expect, AI is everywhere, in a variety of formats and functions; we saw many startups using Snowflake Cortex AI and Cortex Agents, as well as interesting applications of LLMs, retrieval-augmented generation (RAG), generative AI and more. Just as interesting is the breadth of use cases — we saw apps for everything from agriculture, self-service analytics and cybersecurity to public health monitoring, virtual 3D labs and supply-chain planning.
Our judges put a lot of careful consideration into selecting the top 10, and we offer our sincere thanks to every company that entered this year. We know how much hard work goes into these submissions, and we appreciate it.
We’re pleased to welcome Sarah Guo, Founder and Managing Partner at Conviction, to the 2025 Snowflake Startup Challenge judging panel. Conviction is a venture firm founded in 2022 to invest in intelligent software, or “Software 3.0” companies.
Sarah is recognized for her expertise in early-stage venture capital and will join the rest of our esteemed judges, including Benoit Dageville, Snowflake’s Co-Founder and President of Product; Denise Persson, Snowflake’s CMO; and Lynn Martin, NYSE Group’s President.
The judges have the thrilling responsibility of selecting a Startup Challenge winner and two finalists, who each have the opportunity to receive a share of up to $1 million in investment, as well as global marketing exposure from Snowflake and exclusive mentorship and visibility opportunities from NYSE.
Now that you’re up to date, let’s meet the companies that will compete for the 2025 Snowflake Startup Challenge grand prize!
Katalyze AI predicts deviations, optimizes raw material control and enhances production efficiency — cutting waste and accelerating time to market for biopharma manufacturers. Its Snowflake Native App, Digityze AI, is an AI-powered document intelligence platform that transforms unstructured biomanufacturing documentation into structured, actionable data and manages the document lifecycle. By enabling advanced analytics and centralized document management, Digityze AI helps pharmaceutical manufacturers eliminate data silos and accelerate data sharing.
Digital transformation is an admirable goal, but legacy systems and inefficient processes hold back many companies’ efforts. KAWA combines analytics, automation and AI agents to help enterprises build data apps and AI workflows quickly and achieve their digital transformation goals. It connects structured and unstructured databases across sources and uses a no-code UI or Python for advanced and predictive analytics. AI agents can assist with research, analytics, reconciliation and more — just one part of KAWA’s AI-native platform designed to enable automation with transparency and enterprise-grade security.
Any company with a fleet of vehicles knows that taking a vehicle off the road means potential losses — but it’s even more painful when it’s unplanned and due to inefficient maintenance. Lumilinks’ FleetSense AI seeks to give fleet operators a crystal ball, applying the power of Snowflake and AI to analyze repair invoices, classify parts and process other relevant data to deliver foresight into vehicle failures, optimize repair strategies and enhance fleet performance.
Targeting organizations with complex, fractured data environments who want to derive better value from their data, Prometheux developed a data foundation layer designed to help humans and AI quickly build applications on a virtual knowledge graph of fragmented data. It joins data from various sources, regardless of original format or location and without requiring data to be moved, and applies logic to generate new insights. Users can work with the data by defining business concepts instead of writing database queries, and data structures can be reoptimized without major infrastructure changes as business needs evolve.
PTA Robotics’ AI-powered vineyard disease prediction system leverages drone imagery, Internet of Things data and weather insights to detect vineyard disease risks before symptoms appear. Unlike traditional methods that rely on manual inspections or vegetation indices that show only general plant stress, PTA Robotics uses AI to zero in on underlying causes of vineyard stress. Farmers can take early, targeted action, helping to stop diseases before they significantly affect crop yield. Snowflake’s AI infrastructure allows the company to scale easily, and Secure Data Sharing enables vineyards to collaborate on disease trends while protecting their proprietary data.
Satlyt is building a software platform that networks satellites into a virtual cloud for fast and secure AI-driven edge computing in space, enabling satellite operators to monetize excess compute capacity. It employs Snowpark Container Services to build scalable AI/ML models for satellite data processing and Snowflake AI/ML functions to enable advanced analytics and predictive insights for satellite operators. As a software-only solution, Satlyt avoids the need for proprietary hardware and leverages Federated Satellite Systems to facilitate integration across operators.
Data management is critical when building internal gen AI applications, but it remains a challenge for most companies: Creating a verified source of truth and keeping it up to date with the latest documentation is a highly manual, high-effort task. Sherloq aims to change this by offering a collaborative platform for managing and documenting data analytics workflows. With a collaborative SQL repository, it creates one place for all queries, integrating into existing workflows so users can automatically save, manage and document ad hoc SQL work on top of Snowflake. Sherloq can integrate with Cortex AI and Cortex Analyst to become the data that feeds internal gen AI apps, helping to deliver trustworthy and reliable outcomes.
Tempo is a Snowflake Native App that uses DeepTempo’s Log Language Models (LogLMs) to address customer security pain points and reduce costs by reducing the volume of raw logs that are sent downstream to security information and event management (SIEMs). Tempo helps customers identify security incidents and analyze their scope and severity; the LogLMs help improve accuracy and ability to adapt to new environments as they are exposed to new data distributions. The app was pretrained using enormous quantities of security logs and is particularly focused on the pattern of events, including relative and absolute time.
SoFlo Solar’s SolarSync platform uses real-time AI data analytics and ML to transform underperforming residential solar systems into high-uptime clean energy assets, providing homeowners with savings while creating a virtual power plant network that delivers measurable value to utilities and grid operators. Snowflake underpins the platform’s data infrastructure, from using Snowpark for Python-based data ingestion pipelines to process residential solar telemetry to using Snowflake Document AI to analyze utility bills and identify solar production credit discrepancies.
Whether your mantra is “fail fast” or “try, fail, try again,” experimenting with new features, pipelines and product designs is key to maintaining agility and being able to keep up with changing customer preferences and market trends. Winning Variant offers a Snowflake-native experimentation platform as a Snowflake Native App, allowing customers to run innovative experiments directly inside the AI Data Cloud. Teams can deploy and manage experiments using data available in Snowflake in real time, without having to deal with access to a third-party platform, exfiltrating sensitive conversion data or building complex data pipelines to get the data they need.
In Round 2 of the Snowflake Startup Challenge, each semifinalist will submit an investor pitch video and interview with the judges to discuss the company’s entry, its product and business strategy and how the company would use an investment if selected as the Startup Challenge winner.
Based on this information, the judges will select three finalists, to be announced in May. The finalists will present to the judging panel during the Startup Challenge Finale at Dev Day in San Francisco on June 5. The judges will deliberate live before naming the 2025 Grand Prize winner.
Be there to cheer on your favorite finalist: Register for Dev Day now to see the finale and experience all of the demos, sessions, expert Q&As and hands-on labs designed to help developers build amazing things on Snowflake.
Congratulations to the 10 semifinalists, and best of luck in the second round!
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