In agtech, the gap between the demo and the dirt is where most products quietly die. So before asking a single commercial feedlot to trust our system, we put it on a working feedlot and handed the results to university scientists. That deployment — 60 head across four pens at Tuskegee University, under continuous 24/7 monitoring — is complete and recording. Today we’re opening enrollment for commercial cattle feedlots.
Why a University Feedlot First?
Because claims should be tested by people with every incentive to be skeptical. Under a Sponsored Research Agreement, Tuskegee University’s researchers lead the science, independently validating the platform across cattle, goats, and sheep. The study’s central question is the one every feedlot manager actually cares about: can continuous AI monitoring flag a sick animal earlier and more reliably than the human eye?
We won’t claim those results before the data is in — that’s the whole point of doing validation this way. What we can show you today is everything the deployment itself proved about putting this system on a real yard.
Four Things the Deployment Proves for Your Yard
It installs without infrastructure
Every node at Tuskegee runs on solar power with battery storage, and the imagery travels over a point-to-point wireless link to an on-site AI server. Zero grid connections, zero trenching. If your pens have poles and sunlight, they have what the system needs.
Enrollment happens at the chute you already run
As cattle came through the chute, each animal was enrolled by its noseprint — a permanent biometric mapped to a 99.9% accurate identity. No ear tags to buy, apply, lose, or replace. Processing day is the only touch the system ever needs.
The night shift is covered
Each camera pairs 4K digital with a thermal channel, so detection runs on body heat, not light. The 12-plus dark hours when nobody is riding pens are exactly when the system keeps watching feeding, resting, and movement.
The data never leaves the yard
All video is processed and stored locally, behind the operation’s own firewall. At a university that protects research integrity. At a commercial yard it means close-outs, treatment records, and performance history stay yours — not a packer’s, not a vendor’s.
What It Watches on a Commercial Yard
The system builds a rolling behavioral baseline for every individual animal — identified by noseprint, no tags — and flags deviations with the reason attached:
- Bunk behavior: per-animal bunk visit duration, time spent eating, and bunk occupancy patterns — the feeding-behavior record that surfaces poor converters and cattle going off feed. (It does not weigh feed, and we won’t tell you it does.)
- Water time: trough visitation frequency and duration, animal by animal.
- Movement and rest: mobility, resting duration, and posture changes that precede visible symptoms.
- Social pressure: cattle repeatedly displaced from the bunk — the difference between a sick steer and a bullied one.
- Thermal signature: body-heat anomalies flagged around the clock.
Alerts arrive as a prioritized pull list with evidence attached — “the steer in Pen 3, off feed since yesterday morning, low movement overnight” — so your riders spend their time treating cattle instead of hunting for them. It’s designed to flag at-risk animals up to 72 hours before visible symptoms.
Where We’re Enrolling
We deploy nationwide across the United States. Our field team is headquartered in Southwest Florida, so feedlots and cattle-feeding operations across Florida, the Gulf Coast, and the Southeast can get priority scheduling for site assessments — and the same solar-powered, weather-hardened hardware that rode out Alabama heat and storms is built for exactly those conditions.
Frequently Asked Questions
Is the system available to commercial feedlots now?
Yes. Following the completed deployment at the Tuskegee University research feedlot in June 2026, Livestock Technologies is enrolling commercial cattle feedlots. Site assessments are scheduled through the contact page, with priority scheduling for operations in Florida, the Gulf Coast, and the Southeast.
What did the Tuskegee deployment actually involve?
Sixty head across four pens placed under continuous 24/7 computer-vision monitoring: solar-powered bi-spectrum (4K + thermal) camera nodes, wireless backhaul, an on-site AI server, and per-animal identification via Nose ID biometrics — all installed and hardened for pasture conditions by the Livestock Technologies field team.
Does the system weigh how much feed each animal eats?
No. It measures bunk visit duration, time spent eating, and bunk occupancy patterns per individual animal against that animal’s own baseline. Those behavior records surface poor converters and cattle going off feed without scale-equipped bunks.
How much earlier can it flag a sick animal?
The platform is designed to flag at-risk cattle up to 72 hours before human riders would spot visible symptoms, by detecting deviations in feeding, water time, movement, resting, and thermal signature. The Tuskegee study is now independently validating early-detection performance under a Sponsored Research Agreement, and results will be published as the study progresses.
Ready to see it on your yard?
Tell us about your operation and we’ll walk you through what a deployment looks like — pens, poles, power, and the pull list your crew would wake up to.