The case study that usually gets written about AI agents in customer service focuses on cost reduction: fewer headcount, lower cost per contact, faster handle times. The Floward and Infobip AgentOS deployment tells a different story, one that revenue leaders should read as a capacity and growth signal rather than an efficiency metric.
Floward, the leading online flower and gifting platform in the Middle East and UK, deployed Infobip’s AgentOS platform to rebuild its customer service operations around agentic AI. The results at peak: 13x higher conversation volumes handled on major demand days, 54,000 conversations managed on Valentine’s Day alone, one-minute response times maintained, a 15% reduction in customer service costs, and a 12-percentage-point increase in customer satisfaction scores. The multi-agent system routes conversations to specialized AI agents for address collection, FAQ handling, and order changes, with seamless escalation to live agents when context requires it. The entire system was designed, tested, and deployed in under two months. Lujain Mallosh, Customer Care Senior Manager at Floward, captured the strategic shift: “Scaling customer service no longer means scaling headcount at the same rate.”
For revenue leaders, the 13x surge capacity number is the one to focus on. In a seasonal gifting business, peak demand periods are also peak revenue periods. Historically, the constraint was staffing: you could not economically hire enough agents for a demand spike that lasted three days, so service quality degraded precisely when it mattered most. Infobip AgentOS removed that constraint. The ceiling on conversational capacity became a function of infrastructure, not headcount. That means Floward could capture revenue during peak periods that would previously have been lost to queue abandonment or degraded experience.
The broader implication for B2B revenue teams is that AI agents are graduating from narrow pilots into operational infrastructure that changes what a business can handle. This connects directly to the deployment gap documented in earlier coverage: AI agents have been deployed, but the highest-value customer journeys are still waiting. Floward’s results suggest the technology is ready. The gap now is organizational, specifically in revenue and operations teams recognizing that AI agent capacity is not just a cost line but a revenue expansion lever for moments of peak demand.
Source: Infobip
