The company said the platform is designed to manage surging traffic from both human shoppers and artificial intelligence (AI)-powered buying agents during high-demand events such as product drops, ticket sales and flash promotions. Unlike traditional virtual queues that primarily focus on handling traffic spikes, Priority Protect aims to distinguish between trusted AI agents, malicious bots and legitimate consumers in real time, per the release.
The launch comes as retailers and marketplaces face a new challenge from agentic artificial intelligence systems that can rapidly add products to carts, compare prices across websites and potentially lock up inventory before a purchase is completed. DataDome said traditional fraud and bot-detection systems often intervene too late in the transaction flow, after inventory has already been reserved or checkout processes have started.
DataDome’s new system uses what the company calls “intent-aware” analysis to prioritize traffic and determine which users or agents should gain access during peak-demand periods, according to the release. The platform is part of the company’s broader push into “agent trust” infrastructure, which focuses on authenticating and monitoring AI agents interacting with commerce platforms.
The move reflects a growing shift across commerce and cybersecurity industries as businesses prepare for AI agents to play a larger role in online shopping. Companies including OpenAI, Google and Anthropic have increasingly pushed artificial intelligence systems capable of executing tasks on behalf of users, including researching products, booking services and making purchases.
DataDome, founded in 2015, provides bot protection and cyberfraud prevention tools for websites, mobile apps and APIs. The company previously raised $42 million in Series C funding to expand its AI-driven bot detection platform.
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PYMNTS has reported that the rise of agentic commerce is forcing merchants and payment companies to rethink fraud prevention, authentication and customer experience strategies as AI agents begin acting more independently inside digital transactions.
“As AI-driven transactions scale, fraud threats are evolving just as quickly,” PYMNTS wrote last month. “Traditional detection models rooted in human behavior patterns are increasingly ineffective against machine-speed attacks.”
