Rivr in action
“By incorporating Rivr into our auction process, our SSP has been able to deliver higher quality traffic to each of its demand partners––driving better performance at lower cost,”
-GumGum CTO, Ken Weiner
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Already have a traffic shaping solution in place?
Rivr’s AI library works on top of existing traffic shaping solutions without interference. Rivr’s models can apply recommendations to already filtered traffic in order to further optimize the final outcome.
Enhance profitability with automated demand predications
Rivr’s AI-powered traffic shaping library plugs into your server to improve monetization, increase scalability and strengthen demand-supply relationships.
All while cutting costs and growing revenue.
Drive value across the programmatic chain
Be a source of higher quality traffic for demand partners, and of more revenue for your supply partners. Rivr optimizes your exchange to provide better matches with fewer unfilled requests, improving fill rates and getting the most out of QPS limits.
Focus on what matters to you
Eliminate the need for manual work when onboarding new partners. Rivr's automated filtering & QPS management allows your business teams to focus on more growth oriented activities with your supply and demand partners.
Save costs by reducing waste and inefficiency
Rivr's traffic shaping increases operating margins by decreasing costs of unique, resell and header bidding traffic. By leveraging our AI library engineering teams can substantially reduce the massive waste weighing down the programmatic ad exchange; without sacrificing revenue.
Make auctions work for both sides of your programmatic ecosystem
Over 95% of all programmatic requests are wasted. That's not good for anyone.
Rivr is on a mission to support supply side companies in developing their competitive advantage. This means maximizing financial health & operational efficiency for our partners.
Never worry about QPS limits again
One of our most valuable functions. Rivr allows teams to extract and utilize the demand side's QPS limits in the most granular efficient way. Drawing greater revenues from given thresholds.