Most manufacturers rely on their ERP to run their business. It connects engineering, production, inventory, purchasing, and finance, keeping teams aligned and operations moving.
AI in manufacturing is starting to build on top of that foundation.
Genius Cortex is an AI layer built into Genius ERP. It’s designed to work directly with your system data, helping users find information more easily, reduce manual work, and support better day-to-day decisions without changing how the ERP itself operates.
In practice, that shows up in tools like a built-in chatbot, natural language search, automated data entry, and AI-driven recommendations inside the system.
Genius Cortex makes everyday work inside Genius ERP simpler. It’s built directly into the system by our in-house developers and helps users interact with data more naturally, without changing how Genius itself is structured.
For most users, working in Genius ERP is about interacting with data. You’re searching, filtering, and navigating screens to find what you need. Over time, you get used to how the system is structured and where everything lives.
Genius Cortex doesn’t change that structure, but it changes how you can access it.
One example is our new built-in chatbot. It allows users to ask questions directly inside Genius and get answers based on help files, documentation, and training content. Instead of searching through menus or documents, you can ask a question and get a response in context, within the same screen you’re already working in.
The same idea applies to how Cortex lets you search your data. Instead of building filters manually, you can describe what you’re looking for in plain language — for example, open quotes for a specific region or customer — and Cortex interprets the request and builds the query for you.
The data and results don’t change. You just get there faster.
A big part of what makes Genius Cortex practical is where it sits. It isn’t a separate tool or external platform. It’s part of Genius ERP, working within the same data, workflows, and processes teams already use.
That makes it easier to adopt, because it doesn’t require a new way of working. It builds on what’s already in place.
Another area where Genius Cortex adds value is in how information gets into the system. A lot of important data doesn’t start in Genius. It comes from emails, spreadsheets, or customer requests. Before it can be used, someone has to read it, interpret it, and enter it in the right place.
Cortex helps simplify that step. With features like smart paste, users can copy information from an email or spreadsheet, and the system can extract key details — items, quantities, units — and organize them into the right structure inside the ERP.
The user still reviews and confirms everything, but they’re no longer starting from a blank screen. It’s a small shift, but in a task that happens constantly, it adds up quickly in both time saved and fewer errors.
Communication is part of almost every process in manufacturing, but it doesn’t always live inside the ERP. Customer updates, clarifications, and changes often come through email. Over time, that creates a gap between what’s in the system and the conversations that shaped it.
Genius Cortex is helping to close that gap. With our new Outlook integration, emails can be connected directly to customers, quotes, and orders. Cortex can recognize incoming messages, associate them with the right records, and build a more complete communication history over time.
That makes it easier to understand not just what’s happening, but the context behind it — without having to track everything manually.
One of the most important areas for AI in ERP is decision support.
In purchasing, for example, most systems rely on rules — minimum levels, reorder points, lead times. These are essential, but they don’t always reflect what actually happens in day-to-day operations. In practice, experienced buyers adjust those recommendations all the time. They know which suppliers tend to be late, recognize patterns in demand, and compensate for gaps in the data.
Genius Cortex builds on that reality. Instead of relying only on static rules, it looks at historical data and suggests what to order based on what has actually happened over time. It also indicates how reliable that suggestion is. If demand has been consistent, the recommendation will be more predictable. If it hasn’t, the system highlights that as well.
That gives users a clearer starting point. Instead of relying only on rules or adjusting everything manually, they can review a recommendation that already reflects how the business tends to operate.
Today, a buyer might review a list of items that need to be reordered, check inventory levels, look at recent usage, and adjust quantities based on experience.
With Genius Cortex, that process becomes more guided. The system looks at demand patterns, supplier performance, and ordering history, then suggests what to order and when. It also highlights which recommendations are more predictable and which ones may need closer attention.
The buyer is still in control. But instead of manually pulling together all of that information, they’re reviewing and validating it. That shift — from gathering information to evaluating it — is where a lot of time is saved.
As AI starts to play a bigger role in decisions like this, questions around accuracy and data security naturally come up.
Data accuracy and security are treated as core requirements. Cortex operates within a controlled context, using defined sources such as system data and documentation. This helps reduce the risk of incorrect or irrelevant responses, although like any AI system, it continues to be tested and refined over time.
Data security is also built into our processes and the design of Cortex. Customer data is not used to train shared AI models, and it is stored separately, ensuring that information remains isolated and protected.
These measures are important safeguards for maintaining trust, especially in manufacturing environments where data sensitivity can be high.
In many organizations, experienced team members play a key role in decision-making. They adjust system recommendations based on what they’ve seen in the past — supplier reliability, demand changes, and other real-world factors that aren’t always captured in static rules.
Genius Cortex is designed to work alongside that expertise. By analyzing historical data and identifying patterns, it helps bring some of that knowledge into the system itself. Over time, that can lead to more consistent recommendations and better alignment between system outputs and real-world decisions.
The role of the user doesn’t change. Decisions are still reviewed and validated. But Cortex helps reduce the variability that comes from relying only on individual experience.
AI doesn’t need to change everything to be useful. In an ERP, the biggest impact often comes from smaller improvements — getting to information faster, reducing manual steps, and making decisions with better context.
That’s what Genius Cortex is focused on — helping you get more from the ERP you already rely on.
If you want to see how it works inside Genius ERP, our webinar walks through the features and what’s coming next.
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