Composable data platform provider SoundCommerce unveiled Reactor, an intelligent data “ETLT” pipeline offering breakthrough flexibility to collect, model, analyze and activate mission-critical data in the AI era. Reactor provides fully prepped and modeled data for faster time-to-value for improved decisioning and AI outcomes, while creating cost-efficiencies to tamp down the spiraling costs of enterprise data management.

“Reactor changes the economics of AI-ready data management – shifting the focus of data engineering and analysis teams from ‘plumbing’ to driving high-impact business decisions and actions”

Data capabilities are crucial for organizations to fully realize the potential of generative AI and data activation to drive their business. But today many organizations are only able to leverage 20 percent of their data due to lackluster data optimization strategies. Worse yet, many are encountering exorbitant data engineering and infrastructure costs, with dim returns on these investments.

Businesses are vastly unprepared for growing demands for AI-ready data; a recent study revealed 59% of senior IT decision makers are worried their organizations’ ability to manage data won’t meet generative AI’s demands.

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Reactor automates the onboarding of clean, well-defined data modeled for generative AI, Business Intelligence (BI) analytics and activation. This supports AI-enabled decisioning without the costs, delays and disruption of traditional, disjointed data management approaches.

Leading global enterprises are already realizing significant benefits from Reactor:

“Reactor’s composable solution reduced our time to market for robust and in-depth retail analytics, while simultaneously enabling our internal data teams to focus on integrating our proprietary data to provide a more complete picture of our audience’s interests and commerce needs,” said Robert Gash, Chief Technology Officer of E-Commerce at Hearst.

France Roy, Chief Technology Officer at Balsam Brands, adds, “At Balsam Brands, we know the importance of using trustworthy data to drive world-class experiences for customers and better company performance. With Reactor and Snowflake, we’re building future-proof data infrastructure for machine learning, advanced analytics and data activation. The goal is to make the data and the tools easy and effective for every business stakeholder across our company.”

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Reactor ingests, maps and models data for hosting in today’s modern data warehouses such as Snowflake and Google Cloud BigQuery, making data available for AI, analysis and activation in popular BI and data activation tools and applications. Reactor renders quality data that is natively accessible for Large Language Model (LLM) platforms such as Snowflake Cortex and Google Gemini on Vertex AI – critical to fast, low-cost generative AI enablement for businesses.

Reactor’s pre-built data collectors ingest data from nearly 100 diverse SaaS and on-prem solutions and applications. Data connectors accommodate modern REST and graphql APIs, diverse flat file formats, and direct database connection protocols.

The platform provides an intelligent data pipeline for advanced data onboarding and modeling for key business functions such as acquisition and retention marketing, customer profiling and activation, and product and operations lifecycle management.

Additional benefits include:

• Drag-and-Drop user interface: Build advanced data flows that unify data across sources and schemas with a drag-and-drop interface and simple Excel-like expression language. Connect website data, products, orders, customers, subscriptions, email/sms messaging, digital advertising, ERPs, warehouse management systems, shipping manifest software shipping, etc., with just a few mouse motions.
• Simple, comprehensive and preemptive data semantics layer: Label and map data upon ingest to common definitions and models for shared data understanding, cataloging and governance across systems, functions, departments and partners.
• Future-proof data replay: Immutably log raw data in Reactor for faster processing and “ETLT” modeling, with the ability to remap and reprocess data whenever new use cases arise.
• Lower cost of data infrastructure: Dramatically reduce software license fees, storage and compute costs.

“Reactor changes the economics of AI-ready data management – shifting the focus of data engineering and analysis teams from ‘plumbing’ to driving high-impact business decisions and actions,” said Eric Best, SoundCommerce Founder and CEO. “Now, data teams can simplify complex data challenges to accelerate adoption of generative AI, analytics and data activation to make data more available and useful across the entire enterprise – driving competitive advantage and profitable growth.”