LiveRamp is a leading data collaboration platform that enables brands to responsibly connect and activate first-party data across marketing ecosystems. Unlike traditional identity solutions, LiveRamp offers a neutral, open infrastructure that integrates with NVIDIA AI to accelerate model training and inference (as of 2026). The company was acquired by Publicis in a landmark deal, underscoring its strategic importance in the advertising technology landscape. LiveRamp's focus on consumer privacy and data ethics sets it apart, providing trusted data collaboration for global brands, retailers, and financial services.
This is how you do data collaboration.
Unify fragmented customer data across platforms while maintaining responsible identity resolution.
Resolve and unify your first-party data within hours, with LiveRamp’s Identity Engine.
LiveRamp is hosting its first LAB Demo Day during Advertising Week New York 2026 to showcase over 25 agentic AI use cases built on its identity and governance infrastructure. The event highlights partnerships with companies like OpenAI, Firsthand.ai, and Shopsense.ai to demonstrate AI-driven performance improvements for publishers and platforms.
LiveRamp has integrated its RampID identity resolution service with AWS Elemental MediaTailor Monetization Functions to enable server-side ad insertion for CTV and FAST publishers. This integration allows publishers to attach authenticated identity signals to ad requests directly within the AWS streaming workflow to improve addressability and inventory CPMs.
Connect, segment, and activate your data to maximize media impact.
LiveRamp announced a new integration with Adobe GenStudio for Commerce Media Networks, aimed at bringing commerce purchase data into the workflow for media networks. The release is dated June 23, 2026.
LiveRamp has integrated its Curation service with Google Ad Manager in a closed beta to support addressable and cookieless programmatic advertising. The integration utilizes LiveRamp's RampID and Authenticated Traffic Solution to allow marketers to leverage first-party and market segment data for forecasting and targeting.
LiveRamp has entered into a definitive agreement to acquire data clean room software provider Habu. The acquisition aims to create a unified, interoperable platform for privacy-compliant data collaboration and campaign measurement across clouds and walled gardens.
LiveRamp and Magnite have integrated LiveRamp's RampID identity solution into the Magnite Streaming CTV SSP. This global partnership allows publishers to pass privacy-conscious identifiers to Magnite, enabling advertisers to execute cookieless, omnichannel targeting campaigns and closed-loop measurement across CTV.
LiveRamp implemented a scheduled, CRON-based infrastructure pre-heating strategy to handle DAZN's massive authentication surges during the 2025 FIFA Club World Cup. Rather than relying on reactive Kubernetes metrics, the proactive scaling successfully managed traffic spikes of up to 200,000 requests per second with zero failures. The technical setup also utilized Google Cloud Armor rules as a multi-tenant safeguard to isolate DAZN's traffic and protect other platform users.
LiveRamp has expanded its partnership with Microsoft Advertising to integrate its Clean Room technology, facilitating privacy-centric connected TV (CTV) measurement. The collaboration leverages Microsoft Azure Confidential Compute to allow joint customers to securely connect first-, second-, and third-party data across Microsoft properties.
LiveRamp and OpenX have expanded their partnership to integrate LiveRamp's Conversion API (CAPI) into OpenX's supply-side platform. The integration resolves first-party online and offline transaction data to RampIDs, allowing programmatic advertisers to buy and optimize based on actual business outcomes rather than proxies.
LiveRamp has integrated Apache DataFusion Comet to accelerate Apache Spark performance within its clean room architecture for cross-media data collaboration and ad-tech analytics. By transitioning Spark from JVM-based row-level execution to native columnar execution via Apache Arrow and Rust, the company achieved up to a 50% runtime reduction on complex queries. This technical optimization aims to lower resource overhead and infrastructure costs for brands, publishers, and platforms operating multi-terabyte ad measurement and attribution workloads.
