Revionics, a provider of retail pricing, has unveiled the alpha release of its multi-agent AI pricing system. The live demonstration and innovation showcase took place at the Google Cloud Next 2025 event in Las Vegas.
Revionics’ Aakriti Bhargava, VP of engineering and AI, and Alex Braylan, director, data science and AI, presented a multi-agent pricing system in which intelligent AI agents work together to help retailers solve complex pricing problems and optimize pricing decisions. Revionics said the multi-agent pricing system can understand and interact with users in natural language, making adoption a breeze for individuals of all levels of technical expertise.
“Leveraging Google Cloud’s Agent Development Kit on Vertex AI, Revionics’ pricing agents work in tandem to help retailers unlock a level of productivity, data democratization 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.”
Oettle said the multi-agent AI pricing system can transform several key aspects of retail operations, including pricing team capabilities and scale, how pricing data is utilized across the extended retail enterprise, and how quickly retailers can respond to ever-changing market conditions.
“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,” GM Scott 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.
“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. 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.”
According to Zucker and Oettle, Revionics’ AI pricing agents will be able to:
- Surface suggested actions across all areas of pricing;
- Evaluate user-inputted pricing recommendations, analyze additional scenarios and visualize the impact of pricing decisions; and
- Execute pricing changes in real time.