If you work in the maritime ecosystem, you’ve probably seen the wave of AI buzzwords hitting every sector: Large Language Models (LLMs), AI agents, agentic workflows. They build on one another, but what role does each play in real-world decisions in maritime risk, trade operations, and regulatory enforcement?
For maritime professionals, understanding the difference between LLMs, vertical AI agents, and agentic workflows isn’t about chasing technology trends – it’s about knowing how each supports the task at hand. Whether you’re screening vessels for sanctions exposure, reviewing cargo documentation, or building intelligence reports, these technologies are reshaping how work gets done. But not all AI is created equal, and not every task requires the same approach.
This blog breaks down the key differences, where each technology fits in maritime workflows, and how to stay in full control while letting AI handle the heavy lifting.
LLM: The Foundation of AI Evolution
The Large Language Model (LLM) is the cornerstone for AI evolution and innovation.
It’s a powerful generative technology trained on massive amounts of general text data. It can interpret prompts, generate content, and surface insights, whether that’s summarizing a long report, drafting an email, or explaining a legal clause. In simple terms, LLMs are the foundation. Everything else, from task-oriented agents to full agentic workflows, builds on this ground.
Although LLMs excel at summarizing large volumes of text or extracting insights from complex Excel spreadsheets, their general-purpose nature limits their ability to deliver sustained business value in expert-led domains such as the maritime ecosystem. Because they are trained for broad coverage, they often fall short on the nuances of the maritime industry:
port regulations, vessel behavior patterns, and evolving sanctions regimes.
The key to overcoming these limits is layering domain-specific context-engineering on top of the base level LLM – injecting expert knowledge of maritime data to create real differentiation and a competitive edge. This is the step up to vertical, task-oriented AI agents that translate an LLM’s general capabilities into reliable decisions – paving the way to robust, full agentic workflows.
From Generalization to Context
Moving beyond one-size-fits-all LLMs requires a three-pronged approach: high-quality input data, prompt engineering, and context engineering. High-quality data is the groundwork for any AI capability. A model’s output is only as good as the data it’s fed and trained on, meaning the foundation must be clean, accurate, and validated.
Prompt engineering is the process of crafting effective instructions so the model produces outputs aligned with your domain and requirements. Context engineering is the practice of deciding what goes into the model’s working memory (“context window”) at each step, enabling it to complete longer, multi-step tasks.
While prompts shape the request, context engineering supplies the right information, instructions, and data to fulfill it. These techniques help with LLMs, but they become mission-critical for vertical AI agents.
What’s an AI Agent and When Do You Need One?
Built on top of LLMs, vertical AI agents are designed for specific domains. They combine the capabilities of an LLM with context engineering (feeding them the right background, rules, and knowledge) so they can:
- Understand maritime-specific terminology, regulations, and data sources
- Follow multi-step processes without forgetting earlier steps
- Adjust outputs as new information becomes available
In the maritime world, this means a vertical AI agent can:
- Automate vessel screening across documents, watchlists, and registries
- Monitor fleet behavior for compliance issues in near real time
- Generate daily operations briefings with key insights already highlighted
- Pre-fill risk assessment reports using structured data and historical analysis
Think of them as tireless team members who remove friction, cut through noise, and give you more time for higher-value decisions – without replacing your judgment or expertise.
An agentic workflow is a coordinated system of multiple vertical agents, each with its own role, memory, and context. These workflows enable organizations to automate complex, intricate processes across time, not just one-off tasks.
In maritime operations, this means chaining together agents that each handle part of the workflow: one agent pulls vessel ownership records, another cross-references sanctions lists, a third compiles a risk summary, and a fourth prepares a report. Each agent is given just the right context to move its step forward, and hands off the results to the next.
Agentic workflows bring three key benefits to maritime teams:
- Orchestration: instead of managing isolated AI outputs, you get a coordinated flow that mirrors your real operational process
- Focus and consistency: each agent has a defined job, input, and output, reducing drift and noise
- Scalability: once designed, these agentic workflows can run across fleets, trades, or ports, helping teams cover more ground without adding headcount
Think of it like building an AI-powered operations center: every agent plays a role, every step builds on the last, and every output is ready for human decision-making. With clear thresholds, validation points, and oversight, agentic workflows don’t take decisions out of your hands – they give you faster, smarter tools to stay ahead of risks.
Why This Matters for Maritime Leaders
The maritime ecosystem is navigating a new era of complexity, from volatile trade routes and expanding sanctions to mounting pressure for real-time decisions and risk mitigation. Adopting AI isn’t about chasing trends – it’s about layering the right capabilities to accelerate decision-making without sacrificing control. AI can help you get there, but only if you match the right layer to the right task:
- LLMs can help you cut through complexity, summarize advisories, generate emails, and review legal clauses
- Vertical AI agents enable structured workflows that automate repetitive tasks, like clarifying vessel behavior, facilitating screening, and surfacing key information right when you need it
- Agentic workflows scale this across fleets, trades, or teams, empowering organizations to move faster, stay focused, and act with confidence
How Windward Brings Vertical AI Agents and Workflows to Maritime Operations
At Windward, AI is deeply embedded into how we help maritime organizations operate with speed, accuracy, and control. By combining powerful LLMs with real-time maritime data, behavioral risk models, and structured logic, we deliver vertical Gen AI agents and agentic workflows that reflect how maritime professionals actually work.
MAI Expert™, our Gen AI-powered virtual subject matter expert, is a vertical AI agent that surfaces risk insights, analyzes vessel behavior, and supports time-sensitive decisions, all while maintaining context across steps.
Moving forward, agentic workflow automation connects the dots: scanning documents, tracking fleet movement, monitoring risk signals, and preparing reports, reducing manual overhead and keeping teams focused on what matters most.
This is how AI becomes operational: not generic, but built for the competitive edge, for the fleet, and for the challenges maritime teams face every day.
From Understanding to Action: The AI Path Forward
Every smart decision starts with clarity and scales with the right tools.
LLMs bring speed and clarity to complex information. Vertical AI agents take it a step further, helping teams manage repeatable tasks and surface what matters. When combined into agentic workflows, these tools can mirror entire operational processes, freeing maritime professionals to focus on strategy and oversight.
The key isn’t choosing between human judgment and AI – it’s using AI that fits your mission. The right setup won’t replace decision-makers. It empowers them to move faster, act smarter, and scale what works.
At Windward, we’re building that future with expert-level AI solutions that align with your real-world challenges, from risk screening to fleet-wide operations. Because when your technology works like your team, you stay ahead.
