Smarter Packaging: How AI + Expertise Are Helping Brands Tackle EPR Reporting

Extended Producer Responsibility (EPR) programs—laws that require brands to track, report, and sometimes pay for the end-of-life management of their packaging—are rolling out across the U.S., and companies are struggling to keep up. Reporting requirements vary by state, and for many producers the data burden alone feels overwhelming: knowing what packaging you sold, what materials it’s made of, and how it’s regulated in Oregon versus Minnesota can be a massive, manual task.

Enter Smarter Packaging—a new collaboration between Washburn Consulting and Smarter Sorting, built to make EPR data manageable, defensible, and fast.

The Collaboration

Traditionally, Washburn Consulting has helped brands navigate the policy side of EPR—interpreting requirements, advising cross-functional teams, and preparing strategic compliance plans. But one gap remained: the data piece. Washburn founder Michael Washburn realized that without strong data collection and classification, even the best compliance strategy can fall flat. 

That’s where Smarter Sorting, a leader in AI-powered product classification, comes in.

How the AI-Powered Model Works

Together, the teams built an AI model designed specifically for EPR reporting workflows. The idea is simple but powerful:

• Accept real, imperfect data—from spreadsheets with missing weights to files without UPCs—and fill in the blanks intelligently. 
• Classify materials and break products into components (e.g., bottle body + label + cap), then match those pieces to state-specific EPR material lists. 
• Automate contextual reporting logic, so the tool knows the exact obligations in each jurisdiction. 
• Validate with both machine and human checks, so nothing is reported without expert review. 

Crucially, the model doesn’t stop at classification—it explains itself. Each decision comes with reasoning that helps users understand why a material was labeled a certain way, which can make compliance reports more defensible with regulators.

Beyond Reporting: Smarter Insights

The model also unlocks strategic opportunities, such as:

• Identifying where packaging portfolios are overly concentrated in hard-to-report materials. 
• Suggesting source reduction opportunities by flagging unnecessary or high-impact items.  

And because EPR rules are still evolving rapidly, the system is built to adapt—meaning as new states adopt laws or modify reporting requirements, the tech can be updated without re-inventing the wheel.

Trust, Validation, and Risk Management

Washburn and Smarter Sorting emphasize that this isn’t “AI chat” or an off-the-shelf bot. They designed the model with layers of validation and transparency because in regulatory compliance, accuracy isn’t optional. Every AI finding has to be traceable, explainable, and reviewable before it becomes part of an official EPR submission. 

The Big Picture

Smarter Packaging tackles one of the most painful parts of EPR compliance—the data—with technology built for real-world business complexity. For brands with thousands of SKUs and evolving regulatory obligations, the promise of a system that can normalize, classify, validate, and document reporting data could be a game-changer.

As Washburn and Smarter Sorting continue to refine the model, this work reflects a broader trend: when policy expertise meets tailored AI, companies can both reduce risk and find strategic gains in their sustainability journeys.

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