Every warehouse manager has a list of reports they need and cannot get. Stock movement by SKU and shift. Putaway times by zone. Inbound volumes versus pick rates for the week. The data is in Helm WMS. Turning it into something usable normally means raising a ticket, joining a queue, and waiting. 

Helm WMS now has a different answer. AI App Building, powered by Claude MCP integration, lets you describe the tool you need and build it inside Helm, connected to your live warehouse data, without writing a line of code. 

Here is what it does, how it works, and why it matters for warehouse operations teams. 

What Is AI App Building in Helm WMS? 

AI App Building is a capability built directly into Helm WMS that connects your warehouse data to Claude via MCP (Model Context Protocol) integration. Claude is Anthropic's AI model, and MCP is the protocol that gives it direct, secure access to the data inside your Helm WMS account. 

The result is simple: you describe what you want to see, Claude builds it, and the finished app sits inside Helm ready for your team to use. No development resource required. No separate tool to log into. No spreadsheet to maintain by hand. 

The same capability launched on Voila earlier this year as the Voila AI App Builder. It is now available inside Helm WMS, built for warehouse and fulfilment operations. 

Cross-platform note 

If your operation uses both Helm WMS and Voila, AI App Building is now available on both platforms. The Voila version connects to your shipping and courier data; the Helm version connects to your warehouse data. Both apps live inside their respective platforms, accessible to your team without any additional logins. 

What Can You Build With It? 

The short answer: any internal tool your warehouse operation needs that your current WMS reporting does not already surface. 

Here are some practical examples: 

• Stock movement dashboards showing receipts, despatches, and adjustments by SKU, location, or date range. 

• Inbound performance views tracking goods-in volumes, putaway times, and exceptions by shift or supplier.

• Pick and pack reporting broken down by operative, zone, or order type. 

• Inventory accuracy tools surfacing discrepancy rates and flagging locations that need attention. 

• Exceptions screens showing orders or tasks that need a human decision before they can progress. 

• Shift handover reports giving the incoming team an at-a-glance summary of where the warehouse stands. 

If you can describe the problem clearly, Claude can build a tool that addresses it. The finished app is connected to your live Helm WMS data, not a static snapshot. It updates as your warehouse does. 

How Does It Work? 

Step 1: Describe What You Need 

You do not need to know how to write a prompt or configure an API. Guided inputs walk you through exactly what information is needed. Describe the problem or the view you want in plain language. Helm takes your inputs and handles the rest. 

Step 2: Claude Builds It 

Helm passes your description to Claude via MCP integration. Claude has direct, secure access to your Helm WMS data and builds a working app based on what you have described. You never interact with Claude directly; Helm manages the connection. 

Step 3: Test It Against Your Real Data 

Before anything goes live, the finished app runs in a test environment inside Helm. You can interact with it, check it does what you need, and refine it if necessary. Nothing is published until you are happy with it. 

Step 4: Publish & Use 

Once you confirm it, the app is published inside your Helm WMS account. It sits under your Apps section, accessible to anyone on your account. No link to share. No separate login. It is just there, ready to use. 

Who Is This For? 

AI App Building is built for the people running warehouse operations day to day, not for development teams. 

• Warehouse managers who need visibility their current reporting does not provide and cannot wait weeks for a development ticket to move. 

• Operations directors who want a real-time picture of performance across shifts, teams, or sites without building a business intelligence stack. 

• 3PL operations teams managing multiple clients who need client-specific views without maintaining separate spreadsheets for each. 

• Compliance and stock control teams who need audit-ready reports on demand rather than at month end. 

You do not need technical experience to use this. If you can describe what you need clearly, you can build it. 

Why This Matters for Warehouse Operations 

Warehouse teams have always had a data problem. The data exists. The WMS captures it. But the gap between the data existing and the right person seeing it in a useful format has always required development resource to bridge. 

That gap creates two familiar problems. First, the reports that do get built are usually built once and rarely updated, so they reflect how the operation worked when someone last had time to work on them. Second, the reports that are needed but never quite prioritised end up in spreadsheets, maintained by hand, by people who have better things to do. 

AI App Building closes that gap. It does not replace your WMS or change how your warehouse operates. It removes the dependency on development resource to turn warehouse data into warehouse insight. 

It is part of a broader direction for Helm WMS: building a warehouse management system that adapts to your operation rather than requiring your operation to adapt to it. If you are interested in how Helm approaches warehouse technology more broadly, the Helm WMS features page covers the full picture. 

How Is This Different From Standard WMS Reporting? 

Standard WMS reporting works well for the reports someone designed when the system was configured. Those reports cover the use cases that were anticipated at setup. They rarely cover the questions that come up six months later when the operation has changed, volumes have grown, or a new client has come on board. 

AI App Building does not replace standard reporting. It supplements it. When a question comes up that your existing reports do not answer, you build the tool that answers it rather than working around the gap. 

The key difference is the time it takes. A standard WMS reporting request involves scoping, development, testing, and deployment, often across multiple sprints. An AI-built app takes minutes. It is not a substitute for complex custom development, but for the everyday visibility gaps that warehouse teams live with, it is a different category of answer. 

Further Reading 

If you are exploring what AI can do across your fulfilment and despatch operation, the Voila AI App Builder covers the same capability applied to shipping data. For broader context on what Helm WMS can do for your warehouse operation, take a look at the Helm WMS integrations page. 

Want to see it in action? 

Talk to the Helm WMS team about AI App Building and what it could surface from your warehouse data.