Beef doesn’t end at the rail. It ends in a box. Brianna Buseman from Marble breaks down what “pack-off” actually is, why it’s one of the most repetitive and labor-heavy parts of a beef plant, and how Marble uses conveyor systems plus computer vision to identify cuts, track product tied to plant programs, and help plants move boxed beef out the door with more consistency and less chaos. She also gets honest about the hard part in food processing: it’s not just building tech, it’s building tech that survives washdown, cold temps, zero downtime tolerance, and real-world training with high turnover crews.
Links
Marble Technologies - https://www.seemarble.com/
Pack Off Video - https://www.seemarble.com/pack-off
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Takeaways
• Marble focuses on pack-off because it’s repetitive, labor-heavy, and required, but doesn’t add value to the cut itself.
• Computer vision has to be trained. Marble showed cameras hundreds of thousands of images so they can correctly classify cuts.
• Plants already sort carcasses by grades/programs, and Marble helps track product tied to those programs and report usable data back to the plant.
• The goal isn’t “replace people.” It’s helping plants operate through absenteeism, seasonal labor churn, holidays, and disruptions without production falling apart.
• Operator adoption improves when the system is designed to be simple, ergonomic, safe, and easy to train, especially with high turnover.
• Food processing automation has unique constraints: washdown, hot water, chemicals, pressure, then running cold immediately after, with no room for fogged cameras or downtime.
• Beef specs are getting more complex (more variations per cut), and cattle are getting bigger, which increases the need for better logistics and efficiency.
• Data only matters if it becomes actionable. Marble’s value is turning weights/images/outputs into something plants can use to improve decisions and consistency.
• Brianna’s context check: one long-time pack-off worker can box enough beef in a year to feed roughly 330,000 people at average consumption. That’s the scale of labor in this area.
Chapters
00:00 Meet Brianna and what Marble actually is
02:40 Why pack-off is the target: boxed beef, repetition, and labor intensity
03:10 How the cameras “learn” cuts and why training matters
04:10 What Marble tracks: cut ID, program/grade tracking, weights, and reporting back to the plant
09:45 Training and adoption inside plants after installs
11:25 Why ag adoption is slow: “what works” vs “what’s better”
17:20 Consolidation/closures, tough margins, and why efficiency matters
19:20 What success looks like long-term: crawl, walk, run tech adoption
marble, automation, beef processing, meatpacking, pack-off, boxed beef, computer vision, machine learning, food processing technology, plant efficiency, labor shortages, washdown equipment, meat science, USDA grading programs, beef logistics, data in meat plants, adoption of ag technology