Data and Technology

Splice Insights

Articles on the emerging technology that is shaping modern supply chains.

Modern supply chains rely on data and technology to improve visibility, coordination, and decision-making. In this section, we explore the platforms, integrations, and digital tools transforming how logistics and shipping operations are managed. From system connectivity and data standardization to emerging supply chain software solutions, these articles examine the technologies shaping the future of global trade.

Clean data needs to be actionable, not trapped in silos

From Normalized to Optimized: Making Your Clean Data Work Harder

Normalization is a process of removing inconsistencies and redundancies so that all your data coming from various sources follows a consistent structure. This matters because in logistics, we're dealing with dozens of carriers, providers, and partners. But normalization is only the foundation for creating value. Moddule and Splice provide a powerful way to ensure that data sharing between logistics service providers, 3PLs, and their shippers starts with clean, normalized inpu

EDI and API integration is critical to making legacy and current logistics protocols to work together.

The "Hybrid Tax": Why Maintaining Parallel EDI, API and AI Streams is Quietly Killing Innovation

Most logistics providers and shippers are now paying a "Hybrid Tax" because of API and EDI integrations. In 2026, the path forward is "protocol agnosticism," where integration providers like Splice seamlessly marry EDI and API together and apply AI as needed. The goals are to reclaim the time to innovate within your IT and development teams by reducing, if not eliminating, time on integrations and to build a competitive advantage in connectivity.

Compliance is mandatory in supply chain and logistics. Deterministics workflow are better given integration challenges with legacy protocols.

Compliance and Audit in Agent Workflows: What Supply Chain Leaders Need to Know

While the concept of AI "agents" is generating significant buzz, it's critical for logistics professionals to understand the difference between agent-based AI and the more widely adopted workflow automation platforms that dominate today’s enterprise stack. While agent-based AI holds promise, regulated logistics workflows require a cautious, transparent approach. Today’s compliance best practices use workflow automation platforms that support compliance.

The Dual Challenge of Information and Connection Gaps is solved using data translation and interoperability of Splice's integration platform.

Information and Connection Gaps in Global Logistics: Bridging the Divide

In logistics, the "integration problem" is a cocktail of two specific issues. First, the Information Gap: "I don’t know what I need to know." Second is the Connection Gap: "I can’t get the data to where it needs to be." In logistics, these gaps are rarely isolated. They combine to create a black hole that results in demurrage fees, missed sailings, and frustrated customers. Splice offers a suite of compatibility tools, including AI, designed for the fragmented world of freig

LLM Hallucinations in Logistics: Causes and Corrections

LLM hallucinations: We’ll explain what they are, how they impact logistics workflows, and why deterministic automation platforms like ours are still the most reliable approach for real-world operational integrity.

As logistics and supply chain operations explore the promise of agentic AI, cost becomes a critical question: How much does it actually cost to deploy an AI agent at scale? Unlike traditional automation workflows, which are deterministic and often cost-predictable, agentic AI introduces variable costs. It is a different calculation to determine costs.

Cost Modeling for Agentic AI in Logistics: What to Expect When Deploying at Scale

Splice breaks down the core cost drivers of agentic operations, how to model them accurately, and how to evaluate whether an agentic approach is cost-effective for your logistics use case.

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