The Food Agentic Stack
Turning agentic AI from one-off experiments into an enterprise-ready platform you can deploy.
Live in food operations today
+11%
throughput from line optimization
Valicoff Fruit Company
40%
faster compliance gap detection
Live at a frozen fruit processor
5–10%
more output per labor hour
Measured across customer floors
What changes when you run on Terri
CEO and owner
See margin on every unit, not just every month.
Every lot, line and order is visible as it happens, so the decisions that move margin get made on the whole picture.
At single-digit net margins, one point of realized value per unit is a double-digit EBITDA move.
COO and operations leaders
The day stops breaking the plan.
When product grades below plan, an order changes, a line goes down or a truck runs late, the next move is ready the moment it happens, not at end of shift.
+11% throughput from line optimization, live customer result.
CFO and controller
One set of numbers, and an AI plan that isn’t an IT project.
Production, inventory and shipments reconcile across your systems, and every new agent arrives governed, versioned and auditable.
Single sign-on, cloud or on-prem.
Quality and food safety
Audit-ready every day.
CCP records reconcile against every run, labels are verified as the line runs, and a full trace takes minutes instead of a weekend.
40% faster compliance gap detection, live customer result.
Why now
The SaaS-apocalypse is happening now.
Software is becoming something you describe, not something you buy.
- New applications in days
- Any dashboard in minutes
- No waiting on a roadmap
The winners own what sits underneath: the data, the food context and the governance. That’s the Food Agentic Stack.
Every food operation has the same AI problem: the data is everywhere.
Orders live in the ERP. Grades and weights live on the plant floor, pallets and locations in the warehouse system, and loads in the transportation system. Labor hours, QC records and costs each live somewhere else, and spreadsheets fill the gaps in between. AI can only work with what it can see, so until the data is connected, every AI project starts as a data project.
Terri brings all of it into one live data model. Nothing to rip out. Nothing to migrate.
What is an agentic stack?
An agentic stack is everything that has to sit between your systems and an AI agent before the agent is useful, and safe, in a real food business. Reasoning models are the easy part: anyone can rent one. The layers underneath are what make agents work in food.
The Food Agentic Stack is all of it, in one platform, built for food.
Five questions to ask any AI vendor
- Can we build agents without IT?
- Can I see and undo every change?
- Who controls what agents access?
- Does it understand my operation?
- Does it connect to my machines?
- Agents and appsSix pre-built food agents, Reflex Ops to run them as one, and anything you build.
- Reasoning modelsChatGPT, Claude or Gemini, swapped as models improve. Anyone can rent this layer.
The stack underneath: what makes agents work in food
- Agent BuildAgents in hours, whole applications in days, with no dev project.
- Version ControlEvery agent change versioned, tested and reversible.
- Agentic Control PlaneGoverns what each person and agent can see and do.
- Context LayerKnows yield, grade, shelf life and cost, so agents read your operation the way your people do.
- ConnectivityEvery business system, plant floor, warehouse and fleet, live, in one data model.
Your existing systems
Why not just have IT build it on ChatGPT or Claude?
It’s the first question every CFO should ask. An IT team with a reasoning model can build a chatbot or a simple agent in a weekend. What it can’t build in a weekend is the stack underneath: live connections to every system and machine, a context layer that understands food, and the controls that keep every person and every agent inside the same rules.
Five kinds of systems. One has every layer.
| Kind of system | AI-native | Live operations and business data | Context layer | Agent builder | Agentic Control Plane | Food decision engines | Multi-entity |
|---|---|---|---|---|---|---|---|
| Food and produce ERPs | No | No | No | No | No | No | Partial |
| Legacy MES and plant-floor systems | No | No | No | No | No | Partial | No |
| Point solutions | Partial | No | No | No | No | Partial | No |
| Generic AI tools such as ChatGPT, Claude and Copilot | Yes | No | No | Partial | Partial | No | No |
| Terri, the Food Agentic Stack | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Native to the platformPartial: through add-ons or workaroundsNot available
Six agents, ready today.
These are the agents we deploy now, from order to settlement, and Reflex Ops runs them as one. When you need something they don’t do, build it on the same stack.
- 01OrderDemand SensingReads orders, history and market signals to see demand shifts early.
- 02ReceiveQC PlatformLive quality and traceability data, from receiving to shipping.
- 03AllocateDynamic AllocationPuts the right product on the right order, shortest life to fastest channel.
- 04PlanPlanner+Keeps long/short positions and par inventory in balance.
- 05ProduceFloor OptimizerMore output from the same lines, labor and shifts.
- 06SettleGrower Accounting & ReconciliationCloses the books on every lot, from plan to final settlement.
Reflex Ops
Running several agents? Reflex Ops runs them as one.
Reflex Ops is Terri’s orchestration layer. It sees each change as it happens, weighs margin, labor and shelf life, and coordinates every agent around one decision. Your people approve what matters.
A day on the floor
Raw product graded below plan at receiving.
Move three orders to lots that match by size and grade.
Approved- Demand Sensing
- QC Platform
- Dynamic Allocation
- Planner+
- Floor Optimizer
- Grower Accounting
A customer adds three loads for Thursday.
Fill two from inventory and one from tomorrow’s first run, with no overtime.
Approved- Demand Sensing
- QC Platform
- Dynamic Allocation
- Planner+
- Floor Optimizer
- Grower Accounting
Line 2 is down for two hours.
Re-sequence Lines 1 and 3 and move four people from Line 2.
Awaiting approval- Demand Sensing
- QC Platform
- Dynamic Allocation
- Planner+
- Floor Optimizer
- Grower Accounting
Product in Room 4 is aging faster than plan.
Ship lots 118 and 121 first, on the fastest-moving orders.
Queued- Demand Sensing
- QC Platform
- Dynamic Allocation
- Planner+
- Floor Optimizer
- Grower Accounting
Illustrative example.
AI your IT team can sign off on.
- Runs in your environment, cloud or on-prem
- One outbound-only tunnel
- Role-based access for people and agents
- Single sign-on
- Every change versioned and reversible
- SOC 2 coming by Q1 2027
Small percentages. Big margin.
At single-digit net margins, one point of realized value per unit is a double-digit EBITDA move. The product is already bought, the line is already running, and the crew is already on the clock.
$2.5M to $7.5M a year
From 1–3% higher realized value per unit. Modeled from customer baselines and validated during implementation.
Fruit packing
Valicoff Fruit Company: 11% more throughput, same lines
With no new equipment or hires, Floor Optimizer found efficiencies in changeover sequences, line speeds and bin staging, putting 11% more product through the same facility.
11%
Throughput increase
0
New equipment
15%
Less changeover time
Real-time
Line visibility
93 systems, connected through one outbound-only tunnel.
ERPs, plant-floor equipment, labor and harvest, quality, databases, message queues and files. 74 connect self-serve; the rest are configured with you or built on request. Your ERP stays the system of record.
Names and logos belong to their owners and identify the systems Terri reads from or writes to.
Built by food, for food.
AI for this industry has to come from people who know it. Our team has spent decades in agriculture and food, and Terri’s Context Layer already knows what a lot, a grade, a yield and a shelf-life clock mean in each kind of operation.
- ProteinCarcass balance and cut-out yield.
- Prepared & further-processedIngredient yield and label specs.
- FrozenLot grades, run sequencing and compliance.
- Produce & fresh-cutSize, grade and shelf life by lot.
- GrowersGrade, pack-out and settlement on every lot.
- Distributors & wholesalersCode dates, warehouses and loads.
- Retail & groceryFresh orders, shelf life and shrink.
See the Food Agentic Stack on your own systems.
Tell us what you run. We’ll show you your systems connected in Terri, and the first agent we’d build on them.