Mad Engine, a global leader in licensed apparel and accessories, has deployed Vertesia's agentic AI platform as a centralized hub for creative operations, the companies announced June 24, 2026. The move equips the firm-which handles massive volumes of licensed intellectual property-with the governance, asset intelligence, and speed required to scale AI across its workflows.
The Vertesia platform provides model-agnostic infrastructure, allowing Mad Engine to use the right AI models for each task while keeping proprietary data within its own tenant. For a digital asset development company handling sensitive IP, that architecture is critical. It gives creative teams a secure, governed foundation for automation without sacrificing control over how assets are used or stored.
Building a secure, governed foundation
Stefan Born, Sr. Director of AI Solutions at Vertesia, described the operational shift. "Mad Engine's creative operations depend on speed, accuracy, and quality. And the deep understanding of the licensors' requirements. AI is supporting their process, in particular around asset quality," Born said.
"With Vertesia, they are putting creatives in the director's seat by leveraging agentic AI to orchestrate the highly manual and time-intensive aspects of creative work. Reducing friction points and improving previously manual quality control. By strategically integrating automation across the entire asset lifecycle, they have transformed how art is created and utilized."
A phased approach to AI adoption
Mad Engine did not try to overhaul everything at once. The company identified high-impact workflows where AI could deliver measurable value quickly, then built outward in phases. Gary Gaffney, EVP of Technology and Systems at Mad Engine, explained the reasoning.
"We did not want to chase AI use cases one at a time and hope they added up to something bigger," Gaffney said. "With Vertesia, we started with high-value creative workflows like asset ingestion, metadata enrichment and search, then built from there. It's like building a skyscraper one floor at a time: each phase delivers value on its own, but it also strengthens the foundation for everything that comes next."
How asset intelligence speeds creative output
Early wins came from automating asset ingestion and deepening the metadata layer. Teams can now search for assets using natural language or submit a hand-drawn sketch to find visually similar files within the library. This not only enforces brand compliance but also prevents duplicate work. Enriched metadata feeds downstream workflows, helping sales analysis and letting the team use existing assets to generate new art much faster.
The approach mirrors a wider shift toward AI Agents & Automation in creative production, where agents handle repetitive tagging and retrieval so humans can focus on design decisions.
Why this matters for creatives
For creative professionals, the biggest takeaway is the reduction in time spent on low-value, repetitive tasks. When asset tagging and compliance checks are automated, designers can iterate faster, reuse approved work more easily, and get designs to sales teams sooner. The change isn't about replacing creative judgment-it's about removing the friction that slows it down. For teams looking to adopt similar workflows, practical guidance on AI for Creatives can help map where automation fits into the art pipeline without disrupting the core creative process.
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