Revionics Releases Multi-Agent AI Pricing System
Revionics announces alpha release for multi-agent AI pricing system at Google Cloud Next in Vegas.
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Revionics has unveiled the alpha release of its multi-agent AI pricing system. A live demonstration and innovation showcase took place at the Google Cloud Next 2025 event in Las Vegas.
For the first time in a public forum, Revionics’ Aakriti Bhargava, VP of Engineering and AI, and Alex Braylan, Director, Data Science and AI, pulled back the covers on what Revionics has been building – a system in which intelligent AI agents work together to help retailers solve complex pricing problems and optimise pricing decisions. This can understand and interact with users in natural language.
“Leveraging Google Cloud’s Agent Development Kit (ADK) on Vertex AI, our pricing agents work in tandem to help retailers unlock a level of productivity, data democratisation and real-time decisioning that has never been possible before in the retail pricing realm,” said Josh Oettle, SVP of Product Management and Engineering at Revionics.
“Our multi-agent pricing system coordinates across the agents, automating the entire workflow. For example, one agent can quickly tell you which products are priced higher than your competitors, another could forecast the impacts to your business if you matched those prices, and another would apply business rules while executing the price changes.”
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Oettle added, “We believe our multi-agent AI pricing system has the power to transform several key aspects of retail operations, including pricing team capabilities and scale, how pricing data is utilised across the extended retail enterprise, and overall, how quickly retailers can respond to ever-changing market conditions.”
What’s groundbreaking with this alpha release, according to Revionics General Manager Scott Zucker, is that Revionics has taken what it’s best known for – a predictive AI platform for retail pricing – and layered in agentic AI to boost how retailers interact with pricing solutions – and with pricing data.
“When retailers buy an enterprise software solution, part of what they’re buying is the pre-configured workflows that are based on industry best practices and common use cases,” Zucker said.
“While pre-built workflows are important to improve operational efficiency and ensure consistent processes, we have a vision that our customers should be able to interact within the workflows of our solution – and also bypass those workflows entirely by interacting directly with their data and with our AI pricing agents.”
Zucker added, “A pricing manager can tell the Revionics AI pricing agent, ‘Find the products that had the biggest change in elasticity, and change the price of those products by 10% while maintaining a 2% margin. In the above scenario, the pricing agents are able to break down the request into multiple parts, orchestrating across tools and agents, to arrive at the action-phase much faster than a user could, working chronologically and step by step.”
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“We are entering an exciting new era of pricing, where autonomous agents augment the already impressive work of pricing and merchandising teams, driving productivity and enabling retailers to scale their pricing strategies without limits.”
During the presentation at Google Cloud Next, Bhargava and Braylan also emphasised Revionics’ recent launch of Conversational Analytics, a data agent that allows users to ask questions of their data in natural language and take informed actions based on the insights they receive.
This is a foundational component and precursor to the multi-agent pricing system. The plan is to launch this in 2026, which will include availability on Google Agentspace, following tests with pilot customers this year.
“We’re taking retailers on an AI journey with us – from GenAI chatbots to conversational analytics to AI pricing agents,” said Zucker. “As a longtime innovator in AI powered pricing solutions, Revionics remains committed to providing retailers with intelligent, data driven tools to help them thrive in an increasingly complex, resource constrained and fast paced marketplace.”
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