Master data management solutions vendor Stibo Systems has launched ProductGen AI, a new generative AI capability embedded in the company’s Product Experience Data Cloud (PXDC). ProductGen AI transforms how enterprises create, govern, and localize product content, which lets teams move faster, stay compliant, and scale globally with confidence.
The problem that Stibo Systems is addressing here is that enterprises across industries face mounting pressure to deliver accurate, engaging, and localized product content at scale. Manual processes slow time to market, increase costs, and make it harder to meet compliance requirements. For global retailers, manufacturers, and consumer brands, these challenges limit growth and undercut customer trust. Stibo Systems believes that they are well positioned to deal with this issue.
“Historically, Stibo Systems has been recognized as a pioneer in Master Data Management [MDM] – trusted by global brands to manage product, customer, supplier, and location data,” said Neda Nia, Chief Product & Growth Officer at Stibo Systems. “The focus was on mastering data and governing the operations around it.
“What’s changed is that MDM is now seen as a growth enabler,” Nia noted. “With AI transformation top of mind for most companies, the entire MDM category has become essential infrastructure. Here’s why: AI needs trustworthy data to function. Without reliable MDM, enterprise AI initiatives fail. But there’s a second shift happening – AI must also be embedded within MDM itself to drive productivity and fundamentally rethink data workflows. We’re working closely with our customer and partner advisory boards to reimagine these workflows from the ground up.”
Nia said that besides MDM, Stibo Systems has also been a category leader in Product Information Management (PIM), and that they have a unique opportunity to shape the future of product experience.
“Today’s product experience is mostly delivered through product detail pages (PDPs), but we’re moving toward something more dynamic and agent-driven,” she stated. “The way product information needs to be discoverable is changing fundamentally. Imagine AI agents answering questions like “which laptop works best for video editing under $1,200?” instead of customers scrolling static pages. We’ve earned our customers’ trust over decades. That trust gives us the mandate – and the responsibility – to shape what product experience becomes next.”
Nia thinks the way that her job description straddles product and revenue places her in a good position to do this.
“I’ve just stepped into the newly defined role of Chief Product & Growth Officer,” she said. “It unites our Product, Innovation/AI, Commercial Product Strategy and Monetization teams so that what we build directly connects to how the market adopts and scales it. It’s about linking value creation with value capture – bringing Engineering, Product, Marketing, and Sales teams closer together to ensure our innovation translates into a measurable impact for customers and the business. This role reflects an industry shift – customers expect vendors to innovate with them while demonstrating clear ROI. We’re eliminating the handoff between what we build and how it scales. By combining Product and Growth teams, we’re moving MDM out of the “back office” and positioning it as category-essential infrastructure powering digital commerce, sustainability, and AI adoption.”
AI has long been part of Stibo Systems’ platform, mainly through machine learning for matching, classification, and enrichment.
“Since 2021, we’ve scaled that vision significantly,” Nia said. “Back then, AI was an add-on feature. Now, AI is a core product pillar. We use Generative AI and machine learning to accelerate data onboarding, automate enrichment, and ensure mastered data fuels our customers’ own AI initiatives. A recent development is that we’re implementing Model Context Protocol (MCP) servers to make enterprise data accessible at scale to AI systems. This means when our customers deploy AI agents – whether for customer service, procurement, or product recommendations – those agents can access trusted, governed data.
“Our goal is to evolve toward agentic MDM – systems that can act autonomously on behalf of users,” Nia stated. “Our leadership is deeply committed to AI adoption, and we’re focused on ROI for our customers. We deploy AI where it delivers measurable value while building toward fully autonomous systems. This responsible approach means our customers see results, not just experimentation.”
This brings us to ProductGen AI.
“ProductGen AI is our Generative AI capability inside the Product Experience Data Cloud (PXDC),” Nia indicated. “It began as a pilot for product copywriting and quickly evolved into an enterprise-ready solution. It’s built for the enterprise, with governance and approvals embedded from day one. The PXDC is our SaaS platform for onboarding, managing, syndicating, and enriching product data. AI was initially layered on as an accelerator, but today it’s embedded at the core – driving onboarding, governance, and syndication natively. This isn’t a feature you turn on; it’s how the platform works.
“ProductGen AI represents the next step in making data not only trusted but actionable,” Nia indicated. “By embedding generative AI directly into our platform, we’re giving our customers the ability to scale their content creation and governance without sacrificing accuracy or compliance. With business users in control and human-in-the-loop oversight built in, enterprises gain both speed and trust in their data that drives standout customer experience, growth, and innovation.”
Nia said that ProductGen AI has three core components.
The first is preconfigured prompt libraries.
“Tailored for PIM/MDM use cases like product titles, attributes, and SEO content – customers don’t need to experiment with prompts,” she said. “We’re also working with select customers on Answer Engine Optimization (AEO), sometimes also referred to as Generative Engine Optimization (GEO), to ensure product data is optimized for AI-driven search experiences.
The second component is governance and approvals.
“Every AI-generated output flows through workflows, audit trails, and compliance checks – critical for enterprise use where brand consistency and regulatory requirements matter,” Nia stated.
The final component is ongoing updates.
“ProductGen AI evolves continuously with the PXDC roadmap, delivering new industry templates and tuned models so customers don’t have to manage upgrades themselves,” Nia said.
“Customers see value quickly,” she continued. “For example, a retailer onboarding thousands of SKUs cuts manual copywriting from hours to minutes, and a manufacturer localizing data across markets gains speed without sacrificing control. One customer reduced time-to-market by 40% while maintaining full governance over brand messaging. Generative AI is still state of the art – but we pair it with adaptive machine learning to make outputs smarter over time. That combination ensures enterprises get both speed and continuous learning.”
Stibo Systems’ ProductGen AI delivers fully integrated, productized capabilities that go beyond custom-built connectors – with preconfigured prompt libraries, governance and approvals out of the box, and ongoing updates as part of the platform roadmap. This ensures customers benefit from continuous innovation without the complexity or cost of one-off integrations.
Nia said that for partners, this announcement strengthens their market position.
“Our channel includes global systems integrators like Accenture and Deloitte, ISV partners like Microsoft, and regional system integrators worldwide. GSIs now have a compelling AI story to lead with. When Accenture pitches digital transformation, PXDC provides the data foundation that makes it possible. ISVs can deepen ecosystem integration. When Microsoft sells Azure, we ensure their customers’ data is AI-ready from day one. Regional SIs gain a differentiated offering that combines enterprise-grade AI with the governance, their clients’ demand.
“This year everyone’s focus is on building the AI-native enterprise backbone that makes transformation possible,” Nia concluded. “Partners are critical here. They bring domain expertise, integration capabilities, and change management that ensure customers don’t just adopt AI, but succeed with it. The question facing every enterprise isn’t whether to adopt AI – it’s whether their data infrastructure can support it. I am happy to be part of Stibo Systems where we can help these enterprises so that they can win the next decade of growth. We’re here to ensure they have the platform and the story to lead with confidence.”