Snowflake

DataOps is a framework that focuses on improving the quality, speed, and governance of data across organizations. It provides a comprehensive platform that integrates tools for agile automation and Internet of Things (IoT) data compression within cloud environments. The DataOps platform facilitates end-to-end orchestration and management, allowing for continuous integration and delivery, automated testing, and efficient data extraction, loading, and transformation processes. By streamlining these operations, DataOps enhances collaboration among stakeholders, reduces operational costs, and ensures data assurance while maintaining robust governance and security measures. This approach empowers businesses to develop faster and more efficiently, ultimately leading to better decision-making based on high-quality data.

Genesis Computing specializes in providing secure, autonomous AI workers to enterprises through its Genbots Platform, which operates within the Snowflake Data Cloud. The company's software is designed to automate essential tasks for small and medium-sized businesses, facilitating processes such as data analysis, file management, and the execution of SQL queries. By leveraging advanced AI technology, Genesis Computing aims to enhance operational efficiency for its clients.

Quantifind, Inc. is a data science company that specializes in creating on-demand insights platforms aimed at enhancing marketing effectiveness and detecting financial crimes such as money laundering and fraud. Founded in 2008 by two Ph.D. graduates in atomic physics, the company offers several key products, including signum Analysis, which helps users assess performance drivers for brands and competitors; signum Voice, which focuses on revenue drivers; and signum Impact, which measures the effects of sponsorships on brand awareness and sales. Additionally, Quantifind's platform integrates internal financial institution data with public domain data to identify risks, thereby assisting financial crime analysts in minimizing false positive alerts and managing risk. The company serves various sectors, including automotive, consumer packaged goods, entertainment, financial services, pharmaceuticals, retail, and telecommunications, and has established a strategic partnership with Oracle Financial Services. Quantifind is headquartered in Menlo Park, California, with additional offices in Silicon Valley, New York, and Washington, D.C.

Datavolo is a Software as a Service (SaaS) company that empowers organizations to leverage their unstructured data effectively. Its core product is a dataflow infrastructure platform, which enables access to all types of data, including unstructured files. This platform captures unstructured data, replaces single-use, point-to-point code with flexible, reusable pipelines, allowing clients to focus on generative AI tasks.

Voyage AI specializes in creating state-of-the-art embedding models and rerankers, designed to enhance the quality, efficiency, and accuracy of unstructured data search and retrieval, particularly in retrieval-augmented generation (RAG) systems. Their solutions, developed by leading researchers, outperform competitors in terms of precision, speed, and cost-effectiveness, and offer flexible deployment options. Voyage AI caters to specific industries like finance, law, and healthcare, providing domain-specific models and custom solutions to meet unique business needs.

Metaplane provides data observability solutions that help organizations build trust in their data. Its platform is utilized by data teams from various notable companies, including Bose and Sotheby's, to streamline engineering processes and proactively address data issues before they escalate. By automatically monitoring modern data infrastructures—from data warehouses to business intelligence dashboards—the platform identifies normal operational behaviors and alerts users when anomalies occur. This capability allows teams to understand data disruptions and implement corrective measures efficiently. Founded by alumni from MIT and HubSpot, Metaplane is supported by prominent investors, including Y Combinator and various tech industry founders. The company's focus is on enabling businesses to act on data insights rather than sifting through information, ultimately reducing customer churn and enhancing upsell opportunities.

Samooha specializes in privacy-enhancing technologies that facilitate secure data collaboration for enterprises. The company aims to democratize access to data, allowing businesses to effectively leverage their data ecosystems. By focusing on secure data sharing, Samooha helps organizations unlock the full potential of their data, generating significant value for enterprises, consumers, and society as a whole.

Ponder Data Inc. specializes in providing enterprise-ready tools that facilitate rapid and flexible experimentation with data at scale. The company's platform is designed to enhance productivity for data teams by enabling them to obtain insights more swiftly, utilizing familiar tools. Ponder's technology focuses on maintaining scalable machine learning and analytics capabilities, allowing users to handle workloads of varying sizes while preserving the user-friendly nature of the pandas API. This approach empowers organizations to perform data science tasks efficiently and effectively, making it easier for teams to derive valuable insights from their data.

BMLL Technologies Ltd. is a financial data company based in London, established in 2014. It operates a cloud-based platform that provides advanced analytics and historical data specifically for capital market participants. The platform utilizes machine learning and inference frameworks to analyze limit order book data from various global financial markets, enabling clients to gain insights into market behavior and forecast price movements. BMLL offers immediate access to standardized Level 3 data, which includes the trading intentions of all market participants, along with pre and post-trade analytics. This service is particularly beneficial for investment banks, hedge funds, asset managers, and academic institutions, allowing them to conduct tasks such as order book simulation, back-testing, risk assessment, and compliance measurement without the need to purchase or curate their own data. BMLL's Data Science as a Service platform is designed for flexibility and scalability, providing users with extensive computational resources and a comprehensive historical record of detailed order book data across various asset classes.

BMLL Technologies Ltd. is a financial data company based in London, established in 2014. It operates a cloud-based platform that provides advanced analytics and historical data specifically for capital market participants. The platform utilizes machine learning and inference frameworks to analyze limit order book data from various global financial markets, enabling clients to gain insights into market behavior and forecast price movements. BMLL offers immediate access to standardized Level 3 data, which includes the trading intentions of all market participants, along with pre and post-trade analytics. This service is particularly beneficial for investment banks, hedge funds, asset managers, and academic institutions, allowing them to conduct tasks such as order book simulation, back-testing, risk assessment, and compliance measurement without the need to purchase or curate their own data. BMLL's Data Science as a Service platform is designed for flexibility and scalability, providing users with extensive computational resources and a comprehensive historical record of detailed order book data across various asset classes.

Reka is an AI research and product company that develops models to benefit humanity, organizations, and enterprises. Reka, based in San Francisco, was founded by Dani Yogatama, Cyprien de Masson d'Autume, Qi Liu, Mikel Artetxe and Yi Tay.

DataOps is a framework that focuses on improving the quality, speed, and governance of data across organizations. It provides a comprehensive platform that integrates tools for agile automation and Internet of Things (IoT) data compression within cloud environments. The DataOps platform facilitates end-to-end orchestration and management, allowing for continuous integration and delivery, automated testing, and efficient data extraction, loading, and transformation processes. By streamlining these operations, DataOps enhances collaboration among stakeholders, reduces operational costs, and ensures data assurance while maintaining robust governance and security measures. This approach empowers businesses to develop faster and more efficiently, ultimately leading to better decision-making based on high-quality data.

LeapYear Technologies, Inc., established in 2014 and headquartered in Berkeley, California, specializes in developing a platform that enables enterprises to securely extract value from their most sensitive data. The platform employs differential privacy, a mathematically proven standard, to protect data while allowing it to be leveraged for machine learning and monetization. LeapYear has collaborated with major corporations across various sectors, including financial services, healthcare, technology, and insurance, to combine, analyze, and securely utilize previously restricted and siloed data sources.

Samooha specializes in privacy-enhancing technologies that facilitate secure data collaboration for enterprises. The company aims to democratize access to data, allowing businesses to effectively leverage their data ecosystems. By focusing on secure data sharing, Samooha helps organizations unlock the full potential of their data, generating significant value for enterprises, consumers, and society as a whole.

Tecton offers an enterprise-ready feature store that addresses the unique data requirements of machine learning. By providing a robust data platform, Tecton enables machine learning teams to efficiently build, serve, and scale features for production use. The platform allows users to construct features from various data sources, including batch, streaming, and real-time data, facilitating the sharing, reuse, and deployment of models. This capability empowers data scientists and organizations to automate decisions at high speed, enhance customer experiences, and transform business processes. Tecton's focus on optimizing the data layer for machine learning aims to help companies develop superior models more rapidly, driving significant business outcomes.

Matillion Ltd. specializes in developing cloud data integration software solutions aimed at helping organizations optimize their data usage. The company offers a range of products, including Matillion ETL for Amazon Redshift and Snowflake, which facilitate the extraction, loading, and transformation of structured and semi-structured data in cloud environments. Additionally, Matillion Data Loader allows users to seamlessly integrate data from various sources into their cloud data warehouses. The Matillion Business Intelligence tool provides self-service reporting and analytics capabilities, while Matillion Exchange serves as a marketplace for users to share and download ETL jobs. Matillion's solutions cater to a diverse clientele, including Fortune 500 companies and mid-sized enterprises across the United Kingdom, the United States, and EMEA. Founded in 2010 and headquartered in Manchester, the company also has offices in New York, Denver, and Seattle.

Domino Data Lab, Inc. offers an enterprise data science platform that supports both on-premise and cloud-based solutions for data analysis applications. Its primary offerings include Domino Cloud, a managed cloud infrastructure for running and scaling models, and Domino On-Premise, which allows clients to track and audit their analyses. The platform is designed to empower data science teams by enabling collaborative, reusable, and reproducible analysis. Domino Data Lab serves a diverse range of industries, including financial services, healthcare, manufacturing, media, technology, retail, and consumer products. The platform is utilized by model-driven organizations to accelerate research, enhance collaboration, and deliver impactful models efficiently. Founded in 2012 and based in San Francisco, California, the company was formerly known as Cerebro, Inc. before rebranding in 2015.

DataOps is a framework that focuses on improving the quality, speed, and governance of data across organizations. It provides a comprehensive platform that integrates tools for agile automation and Internet of Things (IoT) data compression within cloud environments. The DataOps platform facilitates end-to-end orchestration and management, allowing for continuous integration and delivery, automated testing, and efficient data extraction, loading, and transformation processes. By streamlining these operations, DataOps enhances collaboration among stakeholders, reduces operational costs, and ensures data assurance while maintaining robust governance and security measures. This approach empowers businesses to develop faster and more efficiently, ultimately leading to better decision-making based on high-quality data.

Collibra is a data governance software company that provides an end-to-end Data Intelligence platform aimed at facilitating digital business transformation. Founded in 2008 and headquartered in Hoofdstedelijk Gewest, Belgium, Collibra's platform is designed to eliminate traditional data silos, enabling organizations to access and leverage their data effectively. By offering a comprehensive solution that connects data, insights, and algorithms, Collibra empowers users, referred to as Data Citizens, to find the information they need, collaborate efficiently, and understand the data's meaning. This focus on trustworthy business intelligence helps organizations achieve reliable outcomes and optimize their digital operations.

Bodo.ai specializes in providing a high-performance parallel computing platform designed for data analytics, capable of scaling beyond 10,000 cores and managing petabytes of data efficiently. The company’s innovative approach includes automatic parallelization and the first inferential compiler, allowing clients, including Fortune 500 companies, to tackle complex data analysis challenges more quickly and cost-effectively than traditional methods. Bodo.ai's platform retains the simplicity and flexibility of native Python, enabling developers, data scientists, and AI engineers to streamline their workflows while focusing on solving business problems. The platform can be deployed on various infrastructures, from personal laptops to public cloud environments. Headquartered in San Francisco with an additional office in Pittsburgh, Bodo.ai aims to significantly enhance the efficiency of data analytics.

Habu is a marketing data operating system that helps brands enhance their first-party data while prioritizing privacy. The company's modular platform is designed to integrate with existing marketing technologies, including legacy systems, allowing marketers to avoid additional investments in new platforms. Habu enables brands to establish a robust data foundation, uncover actionable insights, and deliver personalized marketing across multiple channels. With its focus on automated privacy compliance, Habu supports clients in navigating the complexities of data management in a privacy-conscious environment. The company is headquartered in San Francisco and has additional offices in Boston and New York.

Anaconda, Inc. is a leading provider of a Python data science platform designed to facilitate the adoption of open data science practices across various industries, including energy, finance, defense, biology, and medicine. Founded in 2011 and headquartered in Austin, Texas, the company offers the Anaconda Distribution, which provides access to essential data science packages, and Anaconda Enterprise, an open data science platform tailored for corporate and academic environments. In addition to its software solutions, Anaconda provides training programs in Python to support individuals transitioning into data science careers, as well as services focused on addressing technical computing challenges related to data management, optimization, and visualization. With a user base exceeding 45 million across 250 countries, Anaconda is recognized as a key player in the data science and AI sectors, serving a significant portion of Fortune 500 companies and fostering a vibrant community around open-source innovation.

Dataiku Inc. is a company that develops a centralized data platform designed to support businesses in their data journey from analytics to enterprise AI. Founded in 2013, and headquartered in New York with additional offices in Paris and London, Dataiku offers a collaborative data science software platform known as Dataiku DSS. This platform enables teams of data scientists, analysts, and engineers to prepare, analyze, and visualize data effectively. It includes tools for data profiling, interactive exploration, and machine learning capabilities, allowing organizations to build and deploy data products efficiently. By providing a repository of best practices and a controlled environment, Dataiku aims to foster collaboration among data professionals and streamline the development of impactful models and innovative solutions. Prominent clients like Unilever and GE utilize Dataiku to enhance their data-driven decision-making processes and adapt to the growing volume of data they manage.

Alation, Inc. is a provider of enterprise data intelligence solutions based in Redwood City, California. Founded in 2012, the company specializes in a platform that facilitates data search and discovery, data governance, data stewardship, and analytics, aiming to support organizations in their digital transformation efforts. Alation's platform is distinguished by its Behavioral Analysis Engine, which integrates machine learning with human insights, enabling effective metadata management and collaboration. This approach empowers users to easily find and understand the data they require, while also ensuring proper governance and compliance. Alation has established itself as a leader in the data catalog market, delivering tools that help analysts make informed decisions by providing a comprehensive view of data usage and provenance.

Dataiku Inc. is a company that develops a centralized data platform designed to support businesses in their data journey from analytics to enterprise AI. Founded in 2013, and headquartered in New York with additional offices in Paris and London, Dataiku offers a collaborative data science software platform known as Dataiku DSS. This platform enables teams of data scientists, analysts, and engineers to prepare, analyze, and visualize data effectively. It includes tools for data profiling, interactive exploration, and machine learning capabilities, allowing organizations to build and deploy data products efficiently. By providing a repository of best practices and a controlled environment, Dataiku aims to foster collaboration among data professionals and streamline the development of impactful models and innovative solutions. Prominent clients like Unilever and GE utilize Dataiku to enhance their data-driven decision-making processes and adapt to the growing volume of data they manage.

Quantifind, Inc. is a data science company that specializes in creating on-demand insights platforms aimed at enhancing marketing effectiveness and detecting financial crimes such as money laundering and fraud. Founded in 2008 by two Ph.D. graduates in atomic physics, the company offers several key products, including signum Analysis, which helps users assess performance drivers for brands and competitors; signum Voice, which focuses on revenue drivers; and signum Impact, which measures the effects of sponsorships on brand awareness and sales. Additionally, Quantifind's platform integrates internal financial institution data with public domain data to identify risks, thereby assisting financial crime analysts in minimizing false positive alerts and managing risk. The company serves various sectors, including automotive, consumer packaged goods, entertainment, financial services, pharmaceuticals, retail, and telecommunications, and has established a strategic partnership with Oracle Financial Services. Quantifind is headquartered in Menlo Park, California, with additional offices in Silicon Valley, New York, and Washington, D.C.

DataRobot, Inc. is a Boston-based company that specializes in developing an automated machine learning platform aimed at empowering enterprises to construct predictive models efficiently. Its offerings include DataRobot Cloud, a cloud-based platform for predictive analytics, and DataRobot MLOps, which facilitates the deployment, monitoring, and management of machine learning models across organizations. Additionally, DataRobot Enterprise provides features tailored for large organizations, such as flexible deployment options, governance, and comprehensive support. The company's solutions cater to a diverse clientele, including business analysts, data scientists, executives, and IT professionals across various sectors such as banking, healthcare, and manufacturing. Founded in 2012, DataRobot has expanded its operations internationally, with locations in London, Paris, Kyiv, Tokyo, and Singapore, and maintains a strategic partnership with Snowflake to enhance its offerings.

CryptoNumerics Inc. is an enterprise software company based in Toronto, Canada, established in 2017. The company specializes in providing solutions that facilitate data analysis while ensuring privacy and compliance with regulations such as HIPAA and GDPR. Its primary offerings include CN-Fuse, which connects and maps decentralized datasets; CN-Shroud, which uses differential privacy techniques to balance re-identification risk and data quality; and CN-Insight, a tool for training machine learning models to predict adverse drug reactions across distributed datasets. By enabling the creation of privacy-protected datasets and allowing for the development of statistical and machine learning models without compromising intellectual property, CryptoNumerics addresses the challenges posed by data restrictions and helps organizations utilize their data more effectively. The company operates as a subsidiary of Snowflake Computing Inc. since July 2020.

HyperFinity provides a data science and machine learning platform designed specifically for retailers, allowing them to leverage data and artificial intelligence for improved decision-making. By offering a user-friendly interface, HyperFinity empowers retail decision-makers to access and utilize advanced analytics without requiring extensive technical expertise. The platform facilitates the optimization of various critical business functions, including product assortment, pricing strategies, marketing efforts, retail media, e-commerce, and supply chain management. Major retailers utilize HyperFinity's solutions to gain valuable customer insights and make informed, data-driven decisions, ultimately enhancing profitability and efficiency in their operations.