QAD | Redzone Expands Agentic AI Strategy Across ERP Operations and Modernization

QAD | Redzone is expanding its agentic AI strategy across both day-to-day manufacturing operations and the longer-term challenge of ERP modernization, introducing new capabilities that aim to help manufacturers automate processes, work more easily with enterprise data and address legacy complexity without waiting for a full core-system transformation.

Announced at Champions of Manufacturing in Chicago, the developments span several parts of the QAD | Redzone portfolio. Champion Assist introduces a natural-language interface within QAD Adaptive ERP, while the new Accounts Payable Champion is designed to automate much of the invoice-to-payment workflow. QAD Source, an ERP-agnostic intelligent sourcing platform built for manufacturing, has also reached general availability with Champion Assist embedded.

Alongside these operational capabilities, QAD | Redzone has introduced Lynx Champion, an agentic AI solution focused on a different but closely related challenge: understanding the years of customizations and embedded business logic that can make legacy ERP modernization difficult to scope, cost and execute.

Taken together, the announcements point to a broader shift in how AI could fit into ERP transformation. Rather than treating AI as something organizations adopt only after modernizing their core systems, QAD | Redzone is positioning it as a technology that can create value within existing environments while also helping manufacturers navigate the modernization process itself.

Moving From Conversational ERP to Autonomous Workflows

Champion Assist is being introduced as a standard capability within Adaptive ERP, giving users a conversational way to interact with enterprise information.

Instead of navigating multiple screens or manually running reports, users can ask questions in natural language. A procurement professional, for example, could ask which blanket orders are approaching expiration, while a finance user could request budget-to-actual information for a particular entity and period.

QAD draws a distinction between this conversational model and its Champions. While Champion Assist responds to users, Champions are designed to operate continuously within defined workflows, completing routine tasks and bringing people into the process when an exception or decision requires human attention.

The new Accounts Payable Champion applies that model to invoice processing. According to QAD | Redzone, it can collect invoices from sources including email, supplier portals and EDI, extract information from different formats, match invoices against purchase orders and receipts, and move successfully matched invoices toward payment. Exceptions such as mismatches, missing receipts and disputes are surfaced for human review.

The development reflects a broader evolution in enterprise AI: from tools primarily designed to help employees find or interpret information toward agents capable of taking responsibility for defined stages of a business process.

Creating AI Value Without Waiting for ERP Replacement

One of the more significant elements of the Accounts Payable Champion is that QAD | Redzone is not restricting it to customers already operating Adaptive ERP.

The company says the agent runs separately from the underlying ERP or MES environment and can work with SAP, Infor, Epicor and QAD ERP systems, including QAD Enterprise Edition versions dating back to 2016.

For manufacturers facing multi-year modernization programs, that changes the sequence in which transformation initiatives could potentially happen. Individual processes may be candidates for AI-driven automation even while the underlying ERP remains in place.

“Manufacturers shouldn’t have to choose between modernizing their ERP and creating value today,” said Amit Sharma, President – Manufacturing ERP at QAD | Redzone.

The argument is an important one for the wider ERP market. Transformation has traditionally been approached as a relatively linear journey: modernize the core, migrate data and processes, and then introduce new layers of automation and intelligence. Agentic AI creates the possibility of a more incremental model in which some operational improvements happen alongside — rather than after — core modernization.

Lynx Champion Takes Aim at Legacy ERP Customizations

If the Accounts Payable Champion addresses what manufacturers can improve before completing an ERP transformation, Lynx Champion focuses on one of the issues that can prevent modernization from getting started in the first place.

Manufacturers can accumulate years or even decades of custom code as ERP environments are adapted around particular workflows, exceptions and industry requirements. Over time, organizations may lose a clear view of why individual customizations exist, which other processes depend on them, and whether they are still needed.

That creates a difficult modernization problem. Removing everything risks losing valuable business logic; carrying everything forward can reproduce legacy complexity in the new environment.

“Lynx Champion is a game changer in ERP modernizations,” Sharma said. “It scans a legacy ERP environment, catalogs every customization in plain English, and classifies each one with a defined next step.”

QAD says Lynx can also re-architect a proportion of custom code, with the objective of preserving necessary business logic while moving toward a more upgrade-safe modern environment.

This is an important distinction. Customization is not automatically synonymous with technical debt. In manufacturing environments especially, some custom processes may represent years of accumulated operational knowledge or support capabilities that differentiate the business. The modernization challenge is determining what should be retained, redesigned or retired.

AWS Partnership Brings Generative AI Into ERP Discovery

QAD | Redzone worked with AWS on the technology underpinning Lynx Champion, using AWS Transform, Amazon Bedrock and other AWS services to analyze legacy environments and support the modernization process.

“ERP modernization is difficult because manufacturers are not simply moving technology — they’re carrying forward years of business logic, operating knowledge, and custom processes embedded in their systems,” said Mike Choe, General Manager – US Automotive & Manufacturing at AWS.

That observation gets to the heart of why ERP modernization can become so complex. The challenge is not simply migrating data or replacing old software. Organizations first need to understand which parts of a heavily customized environment remain valuable to the way the business operates.

AI-assisted discovery could reduce some of the manual effort involved in establishing that picture, allowing technical and business experts to spend more time on the decisions that require human judgment.

From More Than 1,000 Customizations to a Defined Plan

QAD | Redzone points to an engagement with a global contract manufacturer and packager as an early example of the approach.

The manufacturer was operating a QAD ERP environment with more than 1,000 customizations that did not have clearly defined migration paths or associated cost certainty.

According to QAD, Lynx Champion catalogued the environment and produced a categorized inventory, with nearly two-thirds of the customizations receiving a defined migration path on the first pass. Further classification reduced the remaining review queue by approximately three-quarters, the company says.

The engagement ultimately resulted in a phased modernization plan, with QAD reporting that nearly $500,000 in projected savings were identified during the process.

More broadly, QAD says more than 60% of flagged customizations have so far received a clear upgrade path, while early results indicate potential reductions of 25% to 60% in upgrade schedules compared with traditional consulting-led discovery and reimplementation.

Those figures are based on results reported by QAD and will become more meaningful as the technology is applied across a wider range of ERP environments. But the underlying problem Lynx addresses is familiar across the enterprise software market: organizations may know that modernization is necessary while lacking sufficient visibility into the legacy environment to confidently define the journey.

QAD Source Extends the AI Strategy Into Procurement

The announcements also extend QAD | Redzone’s AI strategy into procurement, with QAD Source reaching general availability as a standalone, ERP-agnostic intelligent sourcing platform.

Rather than approaching procurement as a generic purchasing process, QAD Source is designed around manufacturing-specific considerations such as supplier capacity, production-linked lead times, compliance requirements and supply risk.

Champion Assist is embedded natively within QAD Source, giving buyers a conversational interface for working with live sourcing and supplier data. Use cases outlined by QAD include comparing bids across price, terms and compliance requirements; building supplier award recommendations using performance and certification history; monitoring supplier risk; and identifying qualified suppliers according to factors such as category, geography or certification.

The ERP-agnostic model is notable here too. It reinforces the idea that manufacturers do not necessarily need to replace their core ERP before introducing more specialized intelligence around individual processes.

ERP Modernization Is Becoming Less Linear

The larger story behind the announcements is therefore not simply the arrival of several new AI features.

QAD | Redzone is connecting agentic AI to different stages of the ERP lifecycle: interacting with ERP data through natural language, autonomously executing defined workflows, improving sourcing decisions and analyzing the legacy customization landscape that stands between manufacturers and a modern core.

That suggests a less linear model for ERP transformation.

A manufacturer could automate parts of accounts payable while continuing to operate its existing ERP. AI could help analyze the customizations that complicate a future migration. Procurement teams could introduce a specialized sourcing platform alongside the existing technology estate. Core modernization could then proceed with a clearer understanding of what needs to be preserved, redesigned or removed.

None of this removes the harder questions surrounding enterprise AI. Data quality, process design, system integration, governance and human oversight become even more important as AI moves beyond answering questions and begins executing business processes.

But the QAD | Redzone announcements illustrate an increasingly important direction for the ERP market: AI is no longer being positioned simply as one of the benefits waiting at the end of an ERP modernization journey. Increasingly, it is becoming part of the machinery used to get there.