Enterprise system modernization becomes an AI priority
Enterprise system modernization is the process of upgrading, automating, and re-architecting long‑standing ERP and business platforms so they can support AI, faster change, and future digital products without ripping out core systems entirely. This shift is moving from theory to budget line item. Qorelo and Conduct together have raised more than USD 63.5 million (approx. RM292.1 million) to attack the same pain point: legacy system transformation at scale. Their focus is not on replacing SAP or other ERPs but on adding an intelligence layer that makes change faster, safer, and more predictable. This reflects a wider funding trend in AI-powered ERP delivery and enterprise system modernization, where capital is flowing into tools that plug into existing landscapes rather than wholesale replacements. For CIOs, the question is no longer whether to automate ERP and legacy change, but which new AI OS to trust.
Qorelo targets the SAP migration automation crunch
Qorelo has raised USD 3.5 million (approx. RM16.1 million) in seed funding to automate SAP migrations and ERP upgrade workstreams. Its AI-powered platform focuses on SAP migration automation by turning repetitive functional delivery tasks into machine-executable workflows, promising up to 45% shorter project timelines. The timing is deliberate: SAP customers face a 2027 transformation deadline to move to S/4HANA, and many lack enough skilled delivery capacity to complete complex ERP modernization on time. Qorelo positions its intelligence layer as a way to industrialize ERP delivery while creating a continuous system of record for future AI applications. One quotable statement from Qorelo’s co-founder Nicholas Torabi is: “Large enterprises are facing an unprecedented race against time to modernise their digital backbones before the 2027 deadline, but the industry simply lacks the human delivery capacity to make it happen.”
Conduct’s AI OS maps decades of enterprise customisation
Conduct has secured €51 million (USD 60 million, approx. RM276 million) in Series A funding to build what it calls an AI OS for enterprise system modernization. Founded by former Palantir engineers, the platform ingests custom code, configurations, dependencies, and integrations across SAP, Salesforce, Oracle, MES, WMS, and other systems, then maps how these technical components connect to business logic. That mapping lets teams ask practical questions—what depends on a specific approval workflow, which objects a migration affects, or where a pricing rule lives—and then have Conduct generate the code, tests, and implementation steps to change it. According to EU-Startups, teams using Conduct are seeing “acceleration of 30% or more in transformation workstreams and time-to-value for new features.” In effect, Conduct turns opaque, heavily customised landscapes into systems that both humans and AI agents can understand and modify.
AI OS platforms emerge as a new modernization category
Both Qorelo and Conduct sit in a growing category of AI OS platforms built for legacy system transformation. Rather than adding another dashboard or ticketing workflow, these products aim to become the execution layer that connects business intent directly to system change. Qorelo centers on AI-powered ERP delivery for SAP, while Conduct generalizes across ERP, CRM, and industrial systems. Their overlap with other funded players in ERP modernisation, workflow automation, and agent governance points to a shared thesis: the bottleneck in enterprise AI is not model quality but the opacity of existing systems. Investors are backing multiple plays on the same problem, which signals strong market validation for AI-first modernization layers. Over time, these AI OS platforms could become the standard way enterprises plan, approve, and execute change across their most critical software estates.
What the funding surge signals for CIOs and investors
The combined USD 63.5 million (approx. RM292.1 million) in enterprise software funding for Qorelo and Conduct illustrates how central modernization has become to AI strategies. For CIOs facing SAP’s 2027 deadline and sprawling legacy estates, AI-powered ERP delivery tools promise to compress project timelines and reduce dependence on scarce specialists. For investors, the willingness to support several startups solving similar ERP and legacy system transformation challenges suggests a belief that winners may emerge in multiple segments—deep SAP migration automation, cross-stack AI OS platforms, and domain-specific agents. It also confirms a shift away from “rip and replace” thinking toward AI that makes existing systems AI-ready. As more enterprises seek measurable AI results, the platforms that turn decision-to-execution cycles from months into weeks are likely to attract even more capital and become strategic infrastructure.
