TLDR: Samba TV has launched its Snowflake Native App, a new solution for identity resolution that provides advertisers and media platforms with instant and secure access to its proprietary AI-driven graphing algorithms. Available in Snowflake Marketplace and accessed via Snowflake Data Clean Rooms, the app facilitates real-time identity matching and is enabled for Snowflake Cortex AI Agent workflows, aiming to boost accuracy, speed, and privacy in media analytics and optimization.
SAN FRANCISCO – August 14, 2025 – Samba TV, a global leader in AI technology for media analytics, has officially launched its Snowflake Native App, designed to revolutionize identity resolution for advertisers and media platforms. This innovative application offers immediate and secure access to Samba TV’s proprietary graphing algorithms, provided at no additional cost to its clients. The app is readily available in the Snowflake Marketplace and can be accessed through Snowflake Data Clean Rooms.
The new identity solution is engineered to replace traditional, often slow, expensive, and less accurate identity resolution methods with real-time, automated matching capabilities powered by Samba’s extensive AI/ML expertise. This intelligent automation layer is set to empower enterprise marketers by streamlining data collaboration, enabling precise real-time measurement, and significantly enhancing business outcomes through advanced agentic optimization workflows.
Dennis Buchheim, Snowflake’s Global Head of Media, Entertainment, and Adtech/Martech GTM, emphasized the strategic importance of this collaboration: “With the rise of privacy-forward data strategies, partners like Samba TV are helping marketers unlock the value of their first-party data within the Snowflake environment. The Samba TV app, accessible via Snowflake Data Clean Rooms, exemplifies how the AI Data Cloud can enable secure, scalable identity resolution in support of activation, measurement, and analytics use cases that tap into first-party data while maintaining robust data governance.”
The identity matching app allows joint customers to engage in secure data collaboration, leveraging a suite of privacy-forward techniques. These techniques enable the extraction of granular insights without the need to transfer data outside of a Snowflake Clean Room instance. Furthermore, the app is Snowflake Cortex AI Agent-enabled, meaning agents operating within Snowflake can directly access and process data for sophisticated downstream AI agent workflows, ensuring transparency and precision throughout the process.
Ashwin Navin, CEO and Co-founder of Samba TV, highlighted the app’s transformative potential: “Speed, accuracy, and privacy are not often attributes of the data collaboration space, which often settles for ‘better than nothing’ standards of quality. Now we can offer all of these and marry that with a suite of AI Agents that can operate autonomously to drive unparalleled efficiency and performance from the media budget. We’re committed to deploying our solutions wherever companies house their data in a privacy-forward environment; and this Snowflake collaboration delivers on this promise for thousands of Samba and Snowflake customers.”
Also Read:
- Silverpush Enhances Advertising Platform with Advanced Multi-Agent AI System
- Snyk Enhances Security Insights with Cortex AI-Powered Natural Language Chatbot
The foundation of this matching app is Samba TV’s proprietary device graph, which spans millions of smart TVs and digital devices. This provides a unique advantage in identity resolution. By building its Native App on Snowflake, Samba TV ensures seamless interoperability with existing clean rooms, ID frameworks, and modern cloud-native workflows, making it an indispensable tool for data-driven organizations focused on optimizing performance marketing strategies. Samba TV continues to solidify its position as a global leader in AI-driven media intelligence, leveraging first-party data from millions of opted-in connected televisions and billions of web signals across more than 50 countries.
