How A Company Streamlined Marketing Asset Curation Using Databrewery and Brewforce

The company, a leading name in luxury fashion, has always operated at the intersection of bold design and calculated brand storytelling. But with thousands of image assets flowing in from all over the world, the marketing team faced a critical hurdle: how to precisely curate, organize, and deploy those visuals with speed and intelligence. The challenge wasn’t just about volume it was about pinpointing the right image for the right audience at the right time.

To move beyond slow, manual annotation processes, the company adopted Databrewery within its Databricks Lakehouse setup. What followed was a radical shift: campaigns that once relied heavily on data science support now run faster, cleaner, and smarter. Marketing and creative teams can directly access content performance insights, no more waiting on pipelines, no more bottlenecks. The Databricks environment has also consistently outperformed expectations when it comes to infrastructure efficiency and long-term cost savings.

A turning point in creative operations

Before landing on Databrewery, the team tried to make do with open-source tools, hoping to build a functional annotation flow in-house. But as stakeholders like product marketers and brand leads grew more dependent on visual data, the setup couldn’t keep up.

The team soon began searching for a platform that wasn’t just powerful but built for real-world collaboration. Databrewery’s tight integration with Databricks meant the data flowed seamlessly into the existing pipeline, ready to train models and deliver feedback. Brewforce offered the labeling infrastructure needed for high-volume, high-specificity image classification. Within weeks, the system was running in production not just for data teams, but for campaign managers, visual merchandisers, and more.

“The open-source tool worked to some extent, but it created silos,” shared a senior data engineer. “There was no shared interface, no real scalability. Annotating even a thousand images became a logistical mess and results stayed trapped inside someone’s local machine.”

“The game-changer was able to plug Brewforce directly into our S3 storage and have annotated assets flow straight into our modeling framework,” said a lead ML engineer. “That was when we realized we didn’t just buy a tool we unlocked a new way of working.”

The result? Teams can now upload a batch of creative assets, score them against previous campaign performance using a proprietary ranking engine, and get insights in just hours. What used to take two months can now be done before lunch. “We're no longer just reacting to past performance,” explained a brand strategist. “Now, we’re predicting it before the first email even goes out.” The marketing team uses these insights not only to select the best-performing visuals for each region and platform, but also to iterate on creative briefs. “It’s not just about selecting top images anymore, it’s about knowing why they work,” added the strategist.

nternally, the shift was both technical and cultural. Brewforce’s interface helps detect label inconsistencies and spot edge cases that would otherwise derail model performance. “You can’t improve what you can’t see,” said a data ops lead. “Brewforce lets us catch outliers and refine annotations before they affect outcomes.”

Without this system, the company would have needed an entire team just to manage annotation at scale. “I would have had to request at least 10 full-time hires to even attempt this volume manually,” noted one of the data leads. “Instead, we built something smarter and far more sustainable.”

A Tech Foundation That Grows with Ambition

Over time, the Databricks Lakehouse Platform has continued to drive gains across cost, performance, and governance. “What’s surprising isn’t just the performance, it’s how consistently that performance improves,” said a cloud architect. “Even as our user base grows and use cases get more complex, costs have been going down year over year.”

With its robust product roadmap, Databricks has evolved into more than a data platform, it’s the central nervous system for marketing analytics at the company. Add to that the value-based pricing models of both Databrewery and Brewforce, and the company finds itself with technology partners whose incentives are aligned with results.

“We’re not being charged for vanity metrics,” said a marketing ops lead. “We’re paying for what we use and we see real outcomes tied to that usage. That clarity helps us plan for scale without losing control.”

With Databrewery’s smart curation engine and Databricks’ unified infrastructure, the company’s vision for data-driven creativity is no longer aspirational, it’s operational. Teams now act on insights faster, make sharper creative decisions, and deploy visuals with confidence backed by data. The partnership delivers not just faster execution, but better execution.