Food & beverage planning that respects shelf life, allergens and every changeover
Shelf life, CIP and allergen cleans, seasonal peaks, lot traceability — Convect understands the constraints that make food different, and its agents rebalance freshness and cost every time demand or supply moves.
The challenge
What makes food & beverage planning hard
Shelf life is a hard constraint
Ingredients and finished goods both expire. Schedules must respect FEFO and retailers’ minimum remaining shelf life.
Changeovers and cleans add up
CIP and allergen cleans can consume 15–20% of line time. Sequence is everything.
Seasonal swings
Peak season runs out of capacity while the off-season sits idle — annual capacity planning is hard to get right.
Traceability requirements
Food safety rules require end-to-end traceability, so schedules have to carry lot information.
Agents at work
What your planning agents handle in food & beverage
Real situations your planners deal with every week — picked up, analyzed and turned into an explained recommendation without anyone having to notice them first.
A raw-milk delivery arrives short
Disruption Response Agent
Re-allocates supply across plants and SKUs by margin and freshness, and re-sequences fillers to protect key customers.
A retailer moves a promotion forward
Demand Sensing Agent
Picks up the change, re-forecasts the lift, and triggers a replan that still respects remaining-shelf-life rules.
“Why is SKU 2041 short in the Northeast?”
Root-Cause Agent
Traces the gap back through deployment, filler capacity and an allergen clean — and proposes a fix.
Industry ontology
An ontology built for food & beverage
On top of the core model of products, lines, materials and orders, Convect adds the entities and constraints specific to food & beverage — so agents understand your business from day one.
What this means for you
Recipes + lot tracing + clean rules — once these relationships are in the model, the impact of any change (a rush order, a shortage, a breakdown) is traced automatically and handed to the optimizer as constraints.
Shelf-life chain
Ingredient life → production window → finished-goods life → shipping window
Changeover & clean matrix
Product A → B clean times, including allergen levels
Lot traceability graph
Ingredient lot → batch → finished lot → customer shipment
Seasonal demand model
History + weather + holidays + promotions
The decisions we optimize
Strategic, tactical and operational planning — one model
From long-range planning to the shop floor, each layer’s output becomes the next layer’s constraint.
Strategic
Annual / quarterly · resources & network
Annual business plan / S&OP
How much of each category to make where, and how to absorb peak-season gaps early
Capacity planning
New lines, conversions and seasonal capacity reservations
Network & sourcing
Plant–DC service relationships and ingredient allocation across plants
Tactical
Monthly / weekly · quantities & timing
Master production schedule
Weekly volume per SKU per plant, and capacity split across plants
Material requirements
Ingredient and packaging needs and arrival dates, linked to purchasing
Deployment & transport
Plant-to-DC transfers, truck types and loads, balanced against freshness
Operational
Daily / shift · sequence & batches
Line sequencing
Group similar products to minimize CIP and allergen cleans
Batches & shelf life
Batch sizes and latest start times, every batch traceable to ingredient lots
Dynamic replanning
Incremental replans for rush orders, breakdowns and late ingredients
All three layers come from one model: each layer constrains the one below, and execution feedback flows back up — no more three systems with three versions of the truth.
Product preview · Food & beverage · Scheduling
CIP sequence optimization: two fewer cleans, finished earlier
Capabilities
Planning capabilities built for food & beverage
Shelf-life-driven scheduling
Latest start times calculated automatically to protect freshness
CIP & allergen sequencing
Similar products grouped to minimize cleans
Seasonal capacity planning
Annual capacity matched to the forecast, peak needs planned early
Lot-level scheduling
Every batch linked to ingredient lots for full traceability
| Production type | Key constraints | Planning granularity | BOM complexity | Rush-order frequency | Ontology highlights |
|---|---|---|---|---|---|
| Process / batch | Shelf life, CIP / allergen cleans | Batch / shift | Medium (recipes) | Medium (seasonal) | Recipes + lot tracing + clean rules |
See also: Production planning & scheduling · How the platform works
Standards
Configured for food & beverage requirements
During implementation, we configure the model around the quality systems and standards you operate under:
HACCP
Hazard analysis & critical control points
ISO 22000 / FSSC 22000
Food safety management
FDA FSMA
Including Section 204 traceability
BRCGS / SQF
GFSI-benchmarked schemes
Insights
More on food & beverage planning
Agentic AI·Oct 30, 2026
Inside a rush order: what five planning agents do in under two minutes
A walkthrough of one rush order, step by step: which agent picks it up, what it checks, how options are scored — and where the human stays in charge.
Industry insights·Oct 20, 2026
Five reasons the shop floor rejects your plan — and the one root cause
“Not enough clean time.” “The mold’s on the wrong line.” “Parts aren’t here.” Five ways a plan gets sent back, and why they all point to the same gap.
Industry insights·Oct 8, 2026
Food & beverage scheduling: shelf life, allergens and the cost of a bad sequence
Food plants live with constraints discrete manufacturers rarely face. Four of the hardest — and how to turn them into something a solver and an agent can work with.
Put planning agents to work in food & beverage
Get the Food & Beverage Planning Playbook, or talk to a specialist who knows food & beverage planning.