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Decentrix unleashes artificial intelligence for media with BIAnalytix SSP

Decentrix introduced BIAnalytix SSP, a cross-media-capable platform that promises to deliver revenue maximisation opportunities with real-time trading protocols. Built upon Artificial Intelligence for Media (AIfM), the newest addition to the company’s BIAnalytix portfolio enables sophisticated cross-platform media trading at the speed of the buyer.
“BIAnalytix SSP supports cross-platform and real-time trading, with realistic market pricing distilled from the data existing within a media company’s order management systems and processes,” said Taras Bugir, president at Decentrix. “The packaging of cross-media campaign inventory for trading represents a significant milestone in our industry. By addressing complexities that are beyond the reach of human analysis, AIfM enables media organisations — for the first time — to process decisions based upon current and future inventory positions across their entire delivery ecosystem.”
Media companies can use BIAnalytix SSP to begin their transformation to real-time cross-media trading while continuing to leverage existing investments in people, processes, and systems. BIAnalytix SSP boasts functionality in comparison with standard sell-side platforms (SSPs) in the marketplace. The technology leverages a combination of optimisation algorithms orchestrated by machine learning, in turn enabling revenue maximisation opportunities for selected, securely exposed inventory.
BIAnalytix SSP is a repository that integrates all the latest data related to the automated trading of current and future inventory. The platform contains several cross-media components, which together manage inventory, revenues, and budgets, and enable real-time trading and/or pre-negotiated reservation-based trading. It integrates pricing information, contract discounts, and current and forecast inventory capacities, qualified by forecast audiences within relevant audience segments. Additionally, it can calculate future avails for inventory based upon usage and demand pressure and implement policies to manage inventory scarcity, adjusting rate changes accordingly.

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