Versori has released groundbreaking research findings in the ERP space, the research uncovers insight into the strategic focus areas for 2026 by the ERP vendors owning the space.
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Versori has released groundbreaking research findings in the ERP space, featuring project deep dives from the likes of QAD, Syspro, Nominal, Doss and Rillet, the research uncovers insight into the strategic focus areas for 2026 by the ERP vendors owning the space. Versori, the enterprise favourite in AI-Native integrations, has conducted new research into ERP systems, their biggest innovations, and focal areas for next year to continue leading the charge in turning enterprise resource planning into a system of action, rather than that of record.
Syspro’s upcoming AI Studio brings embedded AI agent workers into the ERP experience, allowing customers to use prebuilt agents or create custom ones tailored to their operations. The platform injects intelligence, automation, and decision support directly into everyday workflows.
Driven by customer demand for faster decisions, efficiency gains, and greater operational foresight, Syspro built the studio on world-class AI models to solve industry-specific challenges.
For customers, the impact is immediate: AI-supported decision-making, automated manual tasks, and reduced operational risk, all tuned to manufacturing and distribution needs.
QAD’s Adaptive ERP powered by Champion AI transforms ERP from a system of record into a system of action, using manufacturing-focused AI agents to automate complex workflows and deliver real operational value.
Created to replace the rigidity of traditional ERP, QAD Adaptive brings real-time adaptability that helps customers avoid the ERP “death cycle” and stay agile in fast-changing markets.
Customers benefit from faster go-lives (as little as 90 days), reduced reliance on customisations, smarter operations, and automated low-value tasks, driving higher ROI and workforce productivity.
QAD stands out through its industry-specific design, flexible architecture, and action-first AI. Champion AI agents are built to act, not just analyse, and customers are already seeing significant results, including 74% higher engagement and 32% lower staff turnover.
Nominal’s Transaction Patrol uses AI agents to scan GL data in real time, flag anomalies, and catch finance mistakes before they become costly. Born from Nominal’s own struggle to uncover hidden misclassifications, the tool automates the deep investigative work finance teams normally do manually.
Customers are already seeing impact: Patrol identifies patterns humans miss, reduces time spent reviewing data, and has surfaced hundreds of historic issues in early beta.
Transaction Patrol stands out by replacing rule-based ERP logic with true AI detection, able to spot edge cases, intent, and policy workarounds without heavy configuration or custom code.
DOSS’s Operations Cloud is a composable, AI-native ERP built to handle the real-world chaos of physical operations. It unifies orders, inventory, logistics, production, and finance in one system, goes live in weeks, and lets teams reshape processes in minutes thanks to its proprietary real-time schema architecture.
The platform was inspired by the shared operational pain points across most physical businesses: manual work, poor visibility, and rigid systems, paired with the uniquely messy 20% that traditional ERPs can’t adapt to. DOSS aims to give operators software that fits how the business actually runs.
Customers gain time back, reduce errors, and eliminate reconciliation work, while gaining unified visibility and the ability to adjust workflows without dev tickets or long projects.
DOSS stands out through its real-time composability, on-the-fly schema control, and AI-native design. By unifying data, actions, and analytics across its three native layers (IDP, ARP, DataStudio), it delivers a true single source of truth and developer-level agility without heavy implementations.
Rillet’s Intelligent Agents marketplace brings AI-trained accounting workflows, such as flux analysis, contract creation, and journal entry generation, directly into the ERP, enabling customers to achieve a true zero-day close.
Inspired by the manual workarounds created by disconnected, legacy finance tools, Rillet aims to eliminate spreadsheet chaos and help companies scale with lean accounting teams focused on higher-value work.
Customers are seeing dramatically faster close times and greater scalability, one closed their books by 1:35pm on Day 1, and another scaled from $10M to $100M with only two finance staff thanks to Rillet’s automations.
Rillet stands out as an AI-native ERP. With deep native integrations (Stripe, Salesforce, Ramp, Brex, etc.), it provides clean, structured data that allows its AI agents to execute complex tasks, accelerate the close, and free finance teams for strategic initiatives.
ERP is no longer just the engine pushing the business forward; it’s the path that clears ahead too...
Across every conversation we had for this research, the message was consistent: the future of ERP is simpler, smarter, and more adaptable, built to keep pace with the business, not slow it down.
For years, ERP innovation has been defined by adding more modules, more features, more complexity. But the next wave of platforms is proving that true innovation isn’t about piling on new capabilities. It’s about removing the friction that has long made ERP feel slow, rigid, and difficult to change.
Today’s emerging systems are rewriting that experience.
They’re helping customers go live in weeks, not years. They’re putting real control back in the hands of operators through low-code and modular tooling that teams can shape to fit their workflows. And they’re applying AI where it actually matters:
Just as importantly, these platforms are breaking down the silos that once separated finance, operations, and supply chain. With connected data and integrated processes, teams can finally see the whole picture rather than stitching it together manually. If traditional ERP giants won’t lead this transformation, others already are.
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