AI agents in Infor M3 for order management, item data and customer setup
5 minutes reading
Infor M3 is often the hub of the business. But the data required to make the right decisions and drive the right processes is rarely found only there. It is also in emails, PDFs, customer documents, transport data and other platforms.
Elvenite builds agent solutions that allow M3 to work together with the company's other data and systems. This enables information to be interpreted, verified and turned into action in the right process – automatically or with human oversight where needed.
Summary
AI agents in Infor M3 enable the automation of central processes such as orders, items, and customer data by combining M3 with data from other systems. The result is less manual work, better data quality, and more efficient flows. This is exactly the kind of solutions Elvenite builds for Infor M3.
What are AI agents in Infor M3?
An AI agent in Infor M3 is not just a chatbot or a new interface. It is a guided workflow that can:
- gather information from multiple sources
- interpret both structured and unstructured data
- validate against business rules
- suggest or perform an action in M3
The crucial point is that the agent does not work in isolation. It can retrieve data from the platforms you already use and then act in M3, or in other systems, depending on the process.
This makes a practical difference. M3 changes from being a system waiting for manual input to becoming an active part of a cohesive data landscape.
Read our introduction guide to AI agents here
Four use cases for AI agents in Infor M3
Order agent
An order agent can place orders in Infor M3 based on a prompt, a PDF order, or other incoming information.
This is relevant when order documentation comes in several formats and when manual registration creates unnecessary lead time and risk of errors. The agent can interpret the content, supplement with data from other systems, check against business rules, and then create the order in M3.
The process can be fully automated or built with human-in-the-loop, where a user reviews before the order is finalised.
Item agent
An item agent can set up or update items in Infor M3 based on, for example, prompts, emails, or incoming item information from customers and suppliers.
The important factor here is not just filling in fields. What matters is that item data becomes correct, complete and adapted to your structure in M3. The agent can identify missing information, validate content, and create a more robust item setup. This reduces both manual work and the risk of errors in master data.
Customer agent
A customer agent can set up customers in Infor M3 based on prompts, documentation, or other business information.
In many businesses, customer setup is still a fragmented process with several manual steps, many checks, and varying data quality. An agent can collect documentation, structure the information, validate it against defined requirements, and then suggest or perform the setup in M3.
This results in a faster process and more consistent customer data from the start.
Order optimisation agent
An order optimisation agent can adjust orders in Infor M3 to optimise based on, for example, volume, weight, fill rate, or other transport constraints.
This is a clear example of when AI agents in Infor M3 not only automate administration but improve the decisions themselves. By combining order data in M3 with information from logistics, warehouse, or other platforms, the agent can suggest or carry out better adjustments.
This can lead to more efficient transports, lower costs, and better delivery accuracy.
From automation to human-in-the-loop
Not all processes should be fully automated. This is a common misconception. Some workflows are suitable for direct execution. Others require a user to review and approve before anything is written to M3. That is why we build AI agents in Infor M3 across the entire spectrum.
From fully automated, to human-in-the-loop, to decision support in a user interface. The appropriate level depends on the process's risk, the data quality, and how much control the business needs. This is also where many AI initiatives fail. Not because the technology is lacking, but because the governance is missing.
How our AI agents work in Infor M3 processes
For AI agents in Infor M3 to create value, three things are required:
- First, the agent must understand the process logic, not just the text or document it receives.
- Second, it must be able to use the right data from the right sources, even when the information is outside M3.
- Third, there must be clear rules for when the agent can act independently and when a human should be involved in the loop.
That is why we start with process, data quality and business rules first. Technology is important, but it is not the starting point.
The benefits of AI agents in Infor M3
When M3 can work together with data on other platforms, three things happen:
- You reduce manual work in processes that are currently repetitive and time-consuming.
- You improve the quality of decisions and master data through better validation.
- You create faster and more scalable workflows without losing control.
That is where the real value lies. Not in AI as a concept, but in making business processes work better.
Want to find the right first use case?
The best first step is rarely to start broad. It is to identify a process that is recurring, rule-based, and important enough to deliver clear impact. This is where AI agents in Infor M3 are most useful initially. Would you like to discuss where an agent can create the greatest value in your M3 environment? Contact us and we will identify the right use case, the right data sources, and the right level of automation.
