Dstillery is known for the quality of our AI-powered decisioning products, but what many don’t know is that a few years ago, we completely redesigned our machine learning system from the ground up. The goal was to maximize flexibility so that, amid the uncertainty surrounding cookie deprecation, we could adapt quickly and bring our best-in-class data science ideas to market faster. While cookie deprecation ultimately fizzled out, many of the innovations developed during that period are now driving new and valuable ways to optimize decisioning. This post explores how Dstillery’s modern machine learning platform, MLPipes, enables us to provide our partners with the infrastructure to power some of the most advanced decisioning capabilities in adtech.
Built for flexibility
MLPipes was designed to leverage modern cloud infrastructure, providing the flexibility our Machine Learning Engineering and Data Science teams need to orchestrate use-case-specific algorithms and workflows. We chose tools that are intuitive for our researchers and data scientists, allowing us to rapidly deploy research prototypes that can be continually improved. At the same time, the platform is elastic, enabling us to scale quickly on demand. Because of the design principles behind MLPipes, particularly the separation of policy from mechanism, each solution is built from modular components. This makes MLPipes an ideal platform to support custom workflows for partners, especially as many of them explore agentic orchestration.
We originally built this platform to support new decisioning products we were developing, such as contextual solutions and predictive bidding. These products provide powerful decisioning. In fact, predictive bidding is the most complete expression of Dstillery’s targeting, allowing us not just to inform if an impression is valuable, but also to specify exactly how valuable that impression is at bid time.
From infrastructure to customer innovation
Recently, we’ve partnered with one of the largest food and drug retailers in the United States to deliver a customized predictive bidding solution tailored to their business. Our MLPipes platform allowed us to create a dedicated single-tenant cloud infrastructure – effectively extending their infrastructure with a clean room in which we can tailor our algorithms to their unique first-party data and deliver exactly the right bid price for each opportunity in their campaigns.
While you might expect a custom-tailored solution to take a technical team months of work, the power and simplicity of the MLPipes platform architecture allowed the infrastructure, algorithm, and end-to-end pipeline to be prepared in only a matter of days.
I’m inspired by the value we can create when we bring thoughtful design and modern infrastructure to help solve our partners’ most pressing problems. As we look ahead, even more infrastructure modernization is unfolding here at Dstillery, allowing us to unlock new ways to bring our technology directly into our partners’ environments.
As we help shape the agentic future of adtech, we’re focused on making our AI more accessible, more flexible, and seamlessly integrated into how our partners already work. Whether through custom MCP workflows or our DS-1 interface, or capabilities we haven’t imagined yet, our goal remains the same: to help our partners work faster, make smarter decisions, and unlock more value from their data.