Splice Insights
Technology, Logistics and Supply Chain Perspectives

It’s feasible to create agentic AI for logistics powered by large language models (LLMs). Still, going from concept to a working logistics AI agent is not trivial. It requires a different architecture, and in this article, we break down the components required to build an AI agent for logistics, including what current limitations you need to plan for.

Data integrity is essential for AI in logistics. "Garbage in, garbage out” (GIGO) is more relevant than ever, and logistics data is known to be messy and siloed. That's where an integration platform like Splice has a key role in automating logistics and supply chain processes.

As logistics companies explore artificial intelligence (AI) to increase efficiency and reduce costs, a critical question emerges: What kinds of problems are well-suited to agentic AI? And equally important: Which are not? Agentic AI is most useful when workflows involve unstructured data, unclear instructions, or frequent exceptions. In other cases, use workflow orchestration, a capability inherent in Splice's platform.

As artificial intelligence gains traction in the logistics industry, many supply chain leaders are asking: What is the difference between traditional automation and agent-based AI? More importantly, when should you use one over the other? In this article, we'll explore the distinction between workflow orchestration (deterministic automation) and agentic AI (autonomous, adaptive systems), helping you understand when each approach is best suited for your logistics operation.

Explore what agentic AI actually is, how it differs from traditional workflow automation, and where it fits within the broader landscape of supply chain and logistics technology.

AI in Logistics - Who's wearing rose-colored glasses about? And exporters continue to see challenges managing export receiving dates, and no wonder as 1 in 3 ships are late per Sea Intelligence. We address the systemic issues that go beyond tardy vessels and share a few key reads to keep you on top of resin exports.

There’s a growing belief in logistics that once you’ve built a few APIs, you’re ready for AI. But here’s the truth: AI in logistics doesn’t just need access to data—it needs the right structure, timing, and context. That's where Splice fits in.