Vxceed delivers near real-time intelligence and stronger retail performance using Amazon Bedrock

Vxceed supports CPG companies operating in traditional trade environments, where millions of small, independently run retailers drive most sales. Yet brands often lack real-time visibility into store conditions—whether shelves are stocked, promotions are executed, or field teams are visiting outlets as planned. These blind spots make it difficult to protect shelf space, maintain brand influence, and respond quickly to competitive activity.

These visibility challenges are amplified by the operational realities Vxceed observed across its customers. Large, distributed field forces often face inconsistent training, high turnover, and low compliance with expected workflows. Managers typically rely on end-of-day or weekly reporting, limiting their ability to spot stockouts, missed visits, or execution issues as they occur. And with vast numbers of outlets generating rising volumes of transactional and behavioural data, traditional reporting models cannot keep pace with how quickly market conditions shift.

“If your product isn’t on the shelf when the customer wants it, that sale is gone—and so is the influence you’ve built,” says Cyril Ovely, CTO, and co-founder of Vxceed.

Vxceed set out to build a platform that could interpret store-level signals in real time, identify execution gaps as they emerged, and guide commercial teams with timely, precise actions. Doing so required an environment capable of orchestrating complex AI workflows, scaling to millions of data points daily, and generating insight with minimal latency, setting the foundation for a new solution.

Vxceed built its near real-time, multi-agent AI platform on AWS, extending a long-standing technical relationship that underpins nearly all of its products. “Ninety-five percent of our stack runs on AWS. We’ve been connected with AWS from the beginning, and as a SaaS provider we rely on that expertise to run our infrastructure,” says Ovely.

To shape the platform’s architecture, Vxceed collaborated closely with the AWS Prototyping and Cloud Engineering (PACE) team. “We worked with the AWS PACE team in Australia to build the initial prototype and validate whether the concept was viable and cost-effective,” Ovely explains.

At the core of the solution is a multi-agent architecture powered by Amazon Bedrock. Each agent performs a specialized function—interpreting field signals, summarising patterns, generating narrative explanations, or recommending next steps based on near real-time store conditions. These agents also power Vxceed’s AI-generated news bulletins, short, automated videos that summarize the day’s most relevant risks, opportunities, and execution trends. One agent drafts the script, another produces the audio, another generates the visuals, and the system assembles the components into cohesive updates. “The entire workflow—from generating the script to producing the audio and video—is driven by agents running on AWS, each building a different part of the story,” Ovely says.

Amazon DynamoDB provides the operational backbone for storing visit activity, behavioral data, inventory indicators, and promotional signals from millions of outlets and thousands of field personnel. AWS AppSync WebSockets stream near real-time events into the platform, ensuring new field activity is captured instantly. AWS Lambda and AWS Step Functions orchestrate the ingestion pipeline and coordinate the multi-step Amazon Bedrock agent workflows that transform raw data into structured insight.

Vxceed’s AI-driven execution platform is enabling CPG organisations to shift from delayed, reactive reporting to intraday visibility and proactive field management. By surfacing risks, opportunities, and execution gaps as they emerge, commercial teams can intervene earlier, address stockouts more effectively, and strengthen performance across large, distributed sales forces.

For customers operating at massive scale, the platform processes approximately US$250 million in daily transactions, giving teams a unified and continuously updated view of outlet activity. Major deployments have also expanded outlet data quality and coverage from 1.6 million to more than 2 million outlets within 18 months, improving the reliability of store-level insight.

These capabilities translate into measurable commercial impact. Typical results include 5–10 percent sales uplift and 15–25 percent promotion ROI improvement, driven by faster detection of issues and more precise coaching of field teams. The platform’s 2–3 minute AI-generated news bulletins offer consumable, territory-specific insights that replace the need to navigate multiple dashboards, enabling faster, more informed decision-making across traditional trade markets.

The feature has also resonated strongly with customers. As Ovely notes, “We thought the video capability might just be a nice add-on, but it hit a spot we didn’t expect. People are genuinely interested, and they keep asking for it.”