Gradation Blender by Gradation.ai Unlocks Mix Designs in Seconds

New artificial intelligence tool optimizes the process of choosing aggregate blending parameters

Whether you’re developing a new mix or optimizing an existing one, Gradation Blender by Gradation.ai takes the guesswork out of aggregate blending. The proprietary AI algorithm designed by Christian Seagren, co-founder and CEO of Xmix® Materials, analyzes millions of aggregate combinations in seconds.

With mathematical precision, it iterates through blend scenarios faster than an entire team of lab technicians could in a month. No more spreadsheets or manual calculations—just effortless, data-driven results.

Question: Traditional asphalt mix design has relied on manual calculations, spreadsheets and trial-and-error. What are some of the biggest challenges producers face when trying to achieve the right gradation?

Christian Seagren: When designing a mix at the physical properties level, much of the process depends on the skill of a lab technician to find a blend that meets a spec or desired gradation. An experienced technician, working with familiar aggregates, can often estimate what will work off the top of their head. However, for a newer technician—or even a seasoned one working with unknown materials—the barrier to entry is much higher. This can delay turnaround times for new designs or leave potential quality improvements on the table. Moreover, it limits how precisely a producer can match a desired job mix formula (JMF).

Question: What inspired you to develop Gradation.ai, and how does it change the way producers approach aggregate blending?

Christian Seagren: Like many great ideas, Gradation.ai was born out of repetition. After doing something enough times, you start asking yourself: Is there a better way? That “something” happened to be mix design. I found the process of manually adjusting blend percentages frustratingly slow and rudimentary. Depending on the situation, it could take hours—sometimes even days—to dial in the right material or blend to meet spec. Gradation.ai eliminates the guesswork by automating this process, removing subjectivity and delivering optimized results instantly.

Balance Your Mix Design for Asphalt

Question: Can you walk the reader through how someone in an asphalt lab or plant would use the Gradation Blender in their workflow?

Christian Seagren: It’s an ultra-simple process. You input your target gradation, then enter the gradations of the available materials. Once that’s set, you hit calculate, and the blender provides the exact blend percentages that will mathematically get you as close as possible to your target. This can be used at the start of every new mix design or when optimizing existing blends for better performance or material efficiency.

Question: Beyond efficiency, what are the biggest benefits producers gain by using AI for gradation blending?

Christian Seagren: Producers see multiple benefits, but at the top of the list is time savings. By reducing the blending process from hours to minutes, producers and labs can streamline design timelines and increase throughput. The second major benefit is the accuracy and quality of final blends. AI removes human bias from the equation, allowing for more precise and repeatable results.

Evaluation of the Regressed Air Voids Approach for Mix Design

Question: If you had one message for asphalt producers considering AI for mix design, what would it be?

Christian Seagren: Don’t be afraid! Rather than resisting new tools, we need to embrace them. The asphalt industry, in many ways, lags behind others in adopting technology. AI tools like Gradation.ai allow us to leap forward rather than take small steps.

Question: Closing up, as the brains behind Gradation.ai, what are some things you find fascinating about it?

Christian Seagren: There are two things I find incredibly cool about Gradation.ai.

First, its ability to reverse engineer an existing mix’s JMF. If you know the gradation of a finished asphalt mix and can provide the likely aggregates a producer is using, the AI can back-calculate the exact blend percentages that created that mix.

Second, the way it optimizes blends. Both I and some of our testers have noticed that it often suggests aggregate blends we wouldn’t have considered using—yet they work. This is because the AI operates without bias, focusing purely on optimization. It doesn’t rely on assumptions or intuition—it just finds the best mathematical solution.

Visit gradation.ai to learn more.