Inside Cleo’s vision for an AI-native supply chain that thinks ahead

Central to this approach is what Cleo calls context-aware orchestration. In practice, that means understanding not only what has already happened in a supply chain, but what is likely to happen next. Brunswick describes context as having two dimensions, “Historical insight and forward-looking intelligence. Orders, warehouse activity, transportation events, and partner interactions all need to live in a shared environment rather than in disconnected systems. By pulling these pieces into a single orchestration layer, Cleo aims to move customers away from managing isolated processes and toward managing end-to-end outcomes.”

This same philosophy underpins Cleo’s push toward no-code trading partner onboarding. Traditional onboarding often involves lengthy roadmaps, manual mapping, and repeated testing cycles for each new partner. Cleo is using AI to automate much of that heavy lifting by creating partner profiles from existing integrations, ingesting sample documents, and allowing the system to infer schemas and mappings. Instead of starting from scratch, teams can focus on testing and refinement, dramatically compressing onboarding timelines. Looking further ahead, 

As onboarding accelerates, expectations around ongoing trading partner relationships are also evolving. Real-time relationship management and scorecarding represent a move toward performance-based collaboration, but they also reflect shifting power dynamics. 

Retailers, in particular, often dictate terms and impose penalties, leaving little room for transparency or shared problem-solving. Cleo’s goal is to create a more balanced environment by giving all parties a common view of performance and risk. Early warnings, shared visibility, and automated responses to issues can turn what might have been a costly failure into a manageable exception.

Brunswick cautions, however, “That autonomy must be approached deliberately. Automated error resolution is an important first step, but fully autonomous decision-making requires confidence that AI systems are acting appropriately. Cleo encourages customers to let AI models settle and learn before handing over too much control, especially as the speed of innovation continues to accelerate. What seemed ambitious six months ago is already achievable today, and that pace is reshaping expectations across the industry.”