SHELFCAST · POST-HARVEST INTELLIGENCE
ShelfCastAI predicts remaining shelf life for every batch leaving your vertical farm — and routes it to the buyer who will use it, not waste it.
◆ Powered by USDA postharvest research · Built in Phoenix, AZ
01 · THE BRAIN
The moment produce is harvested, its clock starts. Temperature, variety, handling — ShelfCastAI ingests every variable and calculates exactly how many days, hours, and minutes of life remain in each batch.
LIVE PREDICTION
02 · THE DRIVER
A restaurant that turns greens in 2 days gets a different batch than a distributor who holds for 5. ShelfCastAI matches each batch's remaining life to each buyer's actual consumption speed — before the truck leaves the dock.
03 · THE DECIDER
Farms that mis-route produce lose an estimated $327,000/year. ShelfCastAI makes the right call on every batch, every day — routing by shelf life, not just distance or volume.
$327K
avg annual loss from mis-routing · per mid-size farm
04 · THE ARRIVAL
The batch that would have sat too long at one account instead reaches a kitchen that's ready for it — served fresh, the same week it was cut.
harvest → prediction → routing → table
HOW IT WORKS
Log harvest time, storage temp, and product type. Our model ingests USDA decay curves for 8+ leafy green varieties.
ShelfCastAI calculates remaining shelf life per batch, factoring in temperature drift and transit time to each buyer.
Try our calculator →Get instant routing: which buyer gets which batch based on turnover speed, distance, and their storage conditions.
WHY SHELFCAST
Afresh
Retail ordering optimization
Tells grocery stores how much to order
Works backward from the store
◆ ShelfCastAI
Post-harvest routing intelligence
Predicts shelf life at harvest and routes each batch to the right buyer
Works forward from the farm
OneThird
Optical quality scanning
Scans produce at packing houses to grade quality
Works at the inspection point
Afresh optimizes what stores buy. OneThird grades what packers ship. ShelfCastAI decides where farms send each batch. Three different problems.
EARLY ACCESS
2,000+ units/day operations looking to reduce post-harvest waste and optimize distribution routing.
2 slots remainingMulti-location groups spending $10K+/month on produce seeking to cut waste across kitchens.
3 slots remaining20+ store regions ready to pilot intelligent allocation for locally-sourced produce programs.
a few slots remainingDesign partners receive early access, dedicated onboarding, and preferred pricing.
THE OPPORTUNITY
Global food waste cost annually(UNEP)
Of all food produced is lost or wasted post-harvest
AI food waste management market by 2025, growing 23.8% CAGR
Vertical farms with real-time shelf-life routing today
Sources: UNEP Food Waste Index, FAI Research, USDA ERS
BUILT BY AN OPERATOR
At 80 Acres Farms, I built the system that predicted how long produce stays on shelves and how much goes to waste during packaging. It worked — but it was locked inside one company.
At Intel, I'm a Tech Lead and System Optimization Software Engineer building AI-powered dashboards for semiconductor manufacturing — tracking equipment performance, shift handoffs, and production bottlenecks across 24/7 operations.
ShelfCastAI is what happens when you combine real post-harvest experience with production-grade engineering. I've built intelligence tools inside four different industries. This is the one that needs to exist as a product.
FAQ
How It Works
Your farm logs harvest time as part of standard operating procedure — most vertical farms already timestamp every batch at cut. ShelfCast ingests that timestamp along with the product type and initial storage temperature. If your farm uses any harvest tracking system (even a spreadsheet), we can pull from it. No new workflow required.
Our baseline model uses USDA postharvest research data for leafy greens — the same peer-reviewed decay curves used by food safety labs. Under controlled conditions (which vertical farms provide by definition), predictions are accurate within ±1 day. As we collect real data from your operation, the model calibrates to your specific varieties and handling conditions, improving over time.
No. ShelfCast works with data you already have — harvest timestamps, storage temperatures from your existing cold chain monitors, and delivery schedules. If you have temperature loggers in your delivery vehicles or walk-ins (most food-safe operations do), we can ingest that data. We don't sell hardware. We make your existing data smarter.
We currently model 8 leafy green varieties: butterhead lettuce, baby spinach, basil, arugula, mixed greens, microgreens, tuscan kale, and cilantro. These cover 80%+ of vertical farm output. We're expanding to strawberries, herbs, and tomatoes based on design partner needs. If you grow it in a controlled environment, we can model it.
For Restaurants
Your kitchen manager gets a daily view of every delivery's remaining shelf life, sorted by urgency. The interface tells them exactly what to prep first, what to hold, and what to push to tonight's specials before it turns. Think of it as a smart expiration tracker that prevents your line cooks from reaching for the wrong container.
Honestly — maybe not yet. Our strongest ROI is with restaurant groups running 3+ locations, where surplus at one kitchen can be redistributed to another. If you're a single location doing $8K+/month in produce, the prep sequencing alone can save you $300–500/month. But we'll tell you on our call if it makes sense for your size.
For Farms
Initially, you tell us — or we estimate based on industry benchmarks for the account type (fast-casual restaurant vs. grocery chain vs. distributor). Within 2–4 weeks of real delivery data, ShelfCast learns each account's actual consumption patterns and refines routing automatically. The model gets smarter the longer you use it.
ShelfCast is designed to layer on top of what you already use. We integrate via simple CSV upload, API connection, or direct database sync depending on your setup. If you're currently managing distribution with spreadsheets, we can start there. If you're using an ERP or WMS, we connect to that. Implementation takes days, not months.
For Retail Chains
We work with your existing data infrastructure. Most grocery chains already monitor produce case temperatures for food safety compliance and track POS data for inventory management. ShelfCast connects these two data streams — temperature and velocity — to optimize allocation decisions your distribution team is already making manually.
Phase 1 (Week 1–2): Connect to your existing data feeds — POS, temperature logs, delivery schedules. Phase 2 (Week 3–4): Calibrate predictions against your actual waste data. Phase 3 (Week 5+): Live allocation recommendations to your distribution team. Most regions see measurable waste reduction within the first month. We don't ask you to rip out anything — we sit alongside your existing supply chain tools.
About ShelfCast
Afresh works backward from the grocery store — helping retailers order the right quantity. OneThird uses optical scanning to grade produce quality at packing houses. ShelfCast works forward from the farm — predicting shelf life at harvest and routing each batch to the buyer where it will be consumed, not wasted. We're solving the distribution intelligence problem that sits between the farm and the shelf. Different problem, different customer, complementary technology.
We're currently onboarding design partners in the Phoenix metro area — vertical farms, restaurant groups, and regional grocery operations. If you're in the Southwest and want to be one of our first partners, book a call and we'll tell you if it's a fit. Design partners get early access, dedicated support, and influence over the product roadmap.
Pricing depends on your operation's scale — number of SKUs, accounts, and daily volume. For design partners in our current cohort, we're offering significantly reduced rates in exchange for feedback and a case study. Book a call and we'll give you a transparent quote based on your setup.
We're onboarding design partners in the Phoenix area. Drop your email to get early access and product updates.
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