Food Processing

Recall-ready batch traceability and true lot-level costing.

A food and process manufacturer replaced disconnected spreadsheets with a unified production backbone — versioned recipes, batch-level traceability, and FIFO lot costing that made real margin visible for the first time.

Headline outcome

~25%

reduction in batch rejections

The challenge

Where the business was losing.

Recipes and yields lived in spreadsheets, batch records on paper, and production cost was a moving average that hid where margin actually leaked. A recall would have meant days of manual tracing, and wastage was absorbed silently as overhead.

The audit · 3 weeks

What the audit surfaced.

Before building anything, we mapped the operation. These are the findings that shaped what we built.

F01

Forward and backward tracing of a batch for a recall relied on paper records — slow and often incomplete.

F02

Production cost ran on moving-average logic, so true lot-level cost — and real margin — was never visible.

F03

Wastage during production and transfers was untracked, quietly absorbed as overhead.

What we built

The architecture, and the agents in it.

The data foundation, and the AI agents that turn it into decisions and action.

STEP 01

Recipes & batch traceability

Versioned recipes with sub-recipe support and work orders capturing batch, expiry and grain-aware consumption give full forward and backward traceability — the recall-ready foundation the AI reasons over.

STEP 02

Deviation-prediction agent

Watching process and environmental conditions against each recipe's signature, an agent flags a batch trending toward a known defect before it is compromised — turning quality control from after-the-fact rejection into in-line prevention.

STEP 03

FIFO costing & wastage-anomaly agent

A lot-level FIFO cost ledger ties cost to every batch, and an agent flags abnormal wastage and cost drift by reason code — surfacing the margin leakage conventional ERPs quietly absorb as overhead.

Implementation

Weeks 1–3Recipe/BOM masters + batch execution on the primary line

Weeks 4–7FIFO lot-level costing + structured wastage capture

Weeks 8–10Full traceability + one-click recall and audit readiness

Results

Before → after.

Measured against the baseline the audit established — before and after, on the metrics that move the P&L.

Batch traceability

Paper, partialDigital, full

Production costing

Moving averageFIFO lot-level

Batch rejections

Baseline~25% lower

Wastage

Untracked overheadCaptured by reason

The value created

~25% fewer rejections, wastage recovered

Impact from rejection reduction and wastage recovery, plus the margin decisions unlocked once true lot-level cost became visible.

Batch rejections~25% lowerDeviations caught before the batch is compromised

WastageRecoveredMargin leakage captured by reason code instead of absorbed as overhead

Margin decisionsOn true lot costPricing and mix on FIFO lot cost rather than a moving average

Illustrative engagement. The client is anonymised and the figures are representative of the outcomes we target in this sector — but the capability described is real and deployed. Named, verified case studies replace these as clients approve publication.

Start here

Could this be your operation?

Start with a Business Transformation Audit — a structured working session where we map where AI changes your P&L, prioritised by impact.

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