LEA Dynamic Intelligence is an agentic AI platform that helps teams move faster and make better-informed decisions, scaling from AI recommendations to governed execution.
)
Blog
5 AI Agents that actually solve warehouse problems, not just talk about them
There's no shortage of AI hype in logistics. Every platform promises intelligence, autonomy, transformation. But when you're a shift supervisor staring down a missed cut-off, or an inventory manager buried in spreadsheets trying to reclassify ten thousand SKUs, the gap between what's promised and what's practical feels enormous.
That's the gap LEA Dynamic Intelligence's Built-in Agents were built to close.
These are five ready-to-use AI agents that ship inside LEA Dynamic Intelligence, our Agentic AI platform for warehouse and supply chain execution. They're not concepts on a roadmap or custom consulting projects: they're product templates you activate through configuration, included as part of your LEA Reply subscription.
Before we get into what each agent does, it's worth explaining how we think about authority and governance, because that's where most AI initiatives go wrong.
The LEA AI Agent Authority Model
Most conversations about AI in logistics jump straight to full automation. But the organizations getting real value from AI aren’t chasing maximum autonomy. They’re assigning the right level of authority to each decision.
That’s the thinking behind the LEA AI Agent Authority Model. It draws a clear line between organizational AI maturity — how ready a company is in terms of governance, controls, and trust — and contextual agent authority — the level of decision-making power a specific agent has for a specific process.
The model defines five authority levels: Inform, Recommend, Act, Coordinate, and Governed Autonomy. Each comes with a governed authority envelope that takes into account guardrails, policies, approval flows, and more. This enables organizations to adopt agentic AI step by step, expanding its authority as confidence and operations grow.
We’ll explore the model in depth in a dedicated article. For now, here’s what matters: each of our five LEA Dynamic Intelligence Agents sits at a specific point on that spectrum. Here’s where they sit and why.
Out of Stock Agent
Authority level: Inform — the agent explains the cause; a person acts.
When a shipment position can't be fulfilled, someone has to work out why. That usually means opening several reports, cross-referencing physical stock, allocations, zone statuses, inbound ASNs, and shipment details, piecing together data that lives in different places.
The Out of Stock Agent pulls all of that together. It identifies the cause of stock unavailability, separates true shortages from temporary issues like pending putaways or blocked zones, and delivers a single consolidated diagnosis to your customer service team or outbound supervisor. This takes seconds instead of minutes, without toggling between screens or hunting for clues.
The agent doesn't take action. It gives your people the information they need to take the right action quickly.
Labor Distribution Agent
Authority level: Recommend — the agent proposes; the supervisor decides.
Every experienced supervisor has a feel for when things are going sideways like too much backlog or not enough people in the right places. But that instinct doesn't scale, and it walks out the door at shift change.
This agent looks at the same picture, but with numbers. It identifies bottlenecks in real time, estimates the effort needed to hit your cut-off times, and recommends how to reallocate people to keep things moving. It calculates remaining backlog, works out the throughput rate you need, and computes a pressure index per activity — all from real volumes, current assignments, and historical productivity. Run it on a schedule throughout the day and you'll spot SLA risks before a cut-off is missed, not after.
The decision still sits with your operations manager, but now it's backed by data instead of gut feel.
ABC Rebalancer Agent
Authority level: Recommend — the agent recommends reclassification; a person decides before anything is written back.
Item classification drives picking efficiency, but reclassification is one of those tasks that's permanently overdue. It's tedious, spreadsheet-heavy, and easy to push down the list, until your fastest movers end up in the worst slots.
The ABC Rebalancer Agent recalculates classification from real movement data, computes an access index, and produces a reclassification report with charts. A person reviews and approves the recommendation before any updates are written to the WMS item master. This is continuous optimization without the periodic fire drill.
Dock Scheduling Agent
Authority level: Act — the agent handles the dialogue; a person confirms the booking.
Dock scheduling interfaces tend to be rigid, unintuitive, and frustrating, especially for carriers who don't live inside your systems every day. The Dock Scheduling Agent enables plant planners and carriers to search for and book dock-door slots through natural-language conversation, replacing rigid scheduling interfaces with guided, rule-aware dialogue. It feels less like navigating enterprise software and more like asking a knowledgeable colleague for help. The slot is only written once confirmed.
Lost & Found Agent
Authority level: Recommend — the agent identifies what is happening and flags potential causes; a person decides what action to take.
Triggered when a task is running late, the Lost & Found Agent uses camera input to assess the warehouse floor, identify potential causes of delay, and spot issues like an item blocking an AMR route between stations. It correlates what it finds with warehouse items and active tasks and presents its findings to operators, who decide how to resolve the issue.
For floor operations and automation teams, that's the difference between firefighting and catching problems before they spread. The agent surfaces the right information at the right time, but the decision on what to do next stays with your people.
Why This Matters
)
These agents encode the kind of reasoning that currently lives in the heads of your best people. Packaging it as product capability means decisions stop depending entirely on who happens to be on shift. And because they're product templates rather than project deliverables, activation happens through configuration — not custom development. That cuts time-to-value and removes the unpredictability of bespoke builds.
Across all five, the common thread is proactive exception management: surfacing issues early, with enough context for your teams to act before small problems turn into big ones. Faster diagnosis, smarter allocation, cleaner data, smoother scheduling, earlier detection — each with the right level of authority for the problem at hand.
Agents won't replace your people. They'll give them something they rarely have enough of: time, clarity, and confidence in their next decision.
Explore LEA Dynamic Intelligence
,allowExpansion;Resize,width=660)