AI to cut food waste — and keep every batch traceable?
Yes — when the AI can see your whole operation. Adaptrix connects your ERP, MES and quality systems, explains why waste spikes with explainable attribution, forecasts perishable demand with cross-validated forecasting models, and keeps lot records recall-ready under Regulation (EC) 178/2002 — on a self-hosted local LLM, so recipes and supplier data never go to a third-party AI provider.
See it work
Ask in plain language. Get an explained, cited decision.
One question routes through specialised agents — schema, SQL, forecast, root cause and governance — and lands as an auditable answer with the evidence attached.
Director· Food & beverage workspace
DemoWhy is food-waste percentage creeping above our 5% target?
Director Highanswer in 10.9s
- Analysing waste
- Scanning prep_batches + orders
- Ranking the drivers of the change
- Formatting the explained answer
scan Scan orders · 1.8M rowsfilter Filter perishable lotsaggregate Aggregate waste by segmentrank Rank driver contributions
Over-prep on the dinner daypart accounts for most of the waste.
Why waste movednet +2.6 pts
- 65% of the moveOver-prep · dinner daypart+1.7 pts
- Weekend forecast miss+0.7 pts
- Spoilage+0.2 pts
Adaptrix recommends
- Cut dinner-daypart prep par levels 15%
- Adopt the demand forecast for weekend prep
Projected · back to 5.5% waste within a month
GDPR · checkpoints cleanSQL + provenance attachedAudit logged
Ask a follow-up…
Illustrative scenario shown in a demo workspace — figures for demonstration, not a customer result.
Ask it about your operation
Where is food waste creeping in?
Waste rarely spikes — it creeps. A dinner daypart gets over-prepped, a weekend forecast misses, spoilage nudges upward, and a 5% target quietly becomes 9% before anyone owns the number.
Adaptrix links prep batches, orders, the waste log and inventory, forecasts your waste percentage with a 95% confidence interval, and attributes the rise to signed drivers that sum to the change — down to the daypart and process responsible.
- Catch the creep while it is still a prep-level fix
- See which daypart or process drives it — signed, summing to the move
- Act on a recommendation with the projected recovery attached
Scripted replay with illustrative data — this is the real answer view, not a video.
Q
10.9s·auditedWhy is food-waste percentage creeping above our 5% target?
- Parsing the question — metric, segments, horizon
- Linking 4 connected sources
- Forecasting with a 95% confidence interval
Food Waste · 12 wk actuals + forecast
forecast 11.0%
Why it moves
Over-prep on the dinner daypart accounts for most of the waste.
Forecast11.0%95% CI · 9.7%–12.3% by month-end
- +1.7 ptsOver-prep · dinner daypart · 65% of the move
- +0.7 ptsWeekend forecast miss
- +0.2 ptsSpoilage
Net change= +2.6 pts
Adaptrix recommends
- Cut dinner-daypart prep par levels 15%
- Adopt the demand forecast for weekend prep
Projected · back to 5.5% waste within a month
TraceGDPR · checkpoints cleanSQL + provenance attachedAudit logged
1.05 billion t
of food wasted worldwide in 2022 — nearly one fifth of all food available to consumers
59.2 million t
of food waste generated in the EU in 2022 — 132 kg per inhabitant
19%
of EU food waste arises in processing and manufacturing — inside your four walls
Sources: UNEP Food Waste Index Report 2024; Eurostat, food waste estimates for reference year 2022 (published September 2024). Links below.
The problems that quietly eat a food producer's margin
Six patterns we see across food and beverage operations — each one invisible in aggregate reports, each one expensive.
Waste eats the margin
Trim losses, spoilage, rework and giveaway accumulate across lines and shifts — but the P&L only shows one aggregate shrinkage figure, so nobody can act on it.
Perishable forecasting is unforgiving
Short shelf life punishes every forecast error twice: overproduce and you write stock off; underproduce and the retailer's shelf goes empty.
Recalls under time pressure
Article 18 of Regulation (EC) 178/2002 demands one step back, one step forward for every lot. When records live in spreadsheets, a trace takes days you don't have.
Quality drifts by batch and line
Complaints cluster around specific batches, lines or suppliers — but HACCP and lab data sit in silos, so the pattern is found late or never.
Margin varies wildly by SKU and channel
Promotions, private label and food-service terms pull unit economics apart. Averages hide which products and channels actually earn money.
Seasonality distorts every average
Campaigns, holidays and weather swing demand for fresh products. Planning on last month's average guarantees waste in one week and stockouts in the next.
How Adaptrix works in a food and beverage operation
From connected systems to autonomous alerts — without replacing your ERP or MES.
1
Connect
Adaptrix connects to your ERP, MES, LIMS/quality systems and sales channels read-only. No rip-and-replace, no new master data project.
2
Explain
Agentic, explainable analysis with SHAP explainability answers the real questions: why did waste spike on line 3? Which batch or supplier drives complaints?
3
Forecast
Perishable demand forecasting with cross-validated statistical models per SKU, channel and season — so production plans follow demand, not habit.
4
Act
Autonomous alerts flag waste drivers, batch anomalies and OEE dips as they emerge — before they become write-offs or complaints.
Traceability readiness: a five-point self-check
Where does your operation stand today? Five checkpoints, from lot IDs to waste attribution.
| Checkpoint | Recall-ready looks like | Warning sign |
|---|---|---|
| Lot and batch identifiers | One lot ID follows raw material to shipped product across all systems | IDs re-keyed by hand between ERP, MES and spreadsheets |
| One step back, one step forward | Supplier and customer of any lot retrievable in minutes | Records split across paper, email and local files |
| Mock recall drill | A test recall traces a lot end-to-end within hours | The last drill took days — or was never run |
| HACCP / CCP data | Critical control point readings are digital and queryable | CCP logs on paper, reviewed only when the auditor comes |
| Waste attribution | Waste is booked by cause, line and shift | One generic shrinkage account hides every driver |
Based on the traceability obligations of Article 18, Regulation (EC) 178/2002, and HACCP practice.
Your recipes never leave the building
Food producers protect two things: personal data under the GDPR, and trade secrets — recipes, costings, supplier terms. Adaptrix runs its language models on self-hosted open models, hosted for you in its own EU infrastructure. Nothing is sent to US cloud AI services.
Regulation (EC) 178/2002
Lot and batch records become queryable end-to-end, so one-step-back / one-step-forward answers take minutes, not days.
HACCP
Critical control point data is analyzed continuously for drift and anomalies — not just sampled at audit time.
GDPR & data sovereignty
Self-hosted open models mean no prompts, no records and no personal data go to a third-party AI provider.
Trade secrets
Recipes, formulations and supplier terms are analyzed on Adaptrix's own EU infrastructure. They are never used to train third-party models.
SHAP explainability
Every waste or quality finding is traceable to its drivers — auditable answers instead of black-box scores.
Statistical forecasting models
Proven forecasting models tuned to seasonality, promotions and shelf life — per SKU and per channel.
Fixed annual pricing with €0 per-token: costs stay predictable no matter how many questions your team asks. See pricing
AI analytics for food producers: an honest assessment
Where it pays off
- Explainable answers instead of dashboards: you learn why waste spiked, not just that it did.
- Perishable demand forecasts per SKU and channel reduce both write-offs and empty shelves.
- Recall traces and audit answers in hours instead of days — with your existing records.
- Full data sovereignty at a fixed annual price: no per-token billing, no data egress.
What to consider
- It needs read access to your ERP, MES and quality systems — plan a short integration phase.
- Runs on Adaptrix's EU-hosted managed infrastructure by default; on-premise deployment is planned for Enterprise Plus.
- Forecast quality grows with history: two or more years of sales data give the best results.
Profile: a Spanish premium food producer
IllustrativeA Spanish premium food producer runs its own production and sells through retail, food service and direct channels. Waste is booked as one shrinkage figure, demand planning lives in spreadsheets, and a mock recall takes days. With Adaptrix connected to its ERP and production records, the picture changes:
- Waste (merma) is attributed to specific lines, shifts and causes — instead of one aggregate figure at month-end.
- Perishable demand is forecast per SKU and channel ahead of campaign and holiday peaks.
- A mock-recall lot trace is assembled in hours instead of days, with supplier and customer of each lot documented.
Illustrative scenario based on anonymized engagements. Outcomes depend on data quality, systems and scope; this is not a named customer reference.
“Food waste is a global tragedy. Millions will go hungry today as food is wasted across the world.”
Primary sources referenced on this page:
Related guides and solutions
Go deeper on sovereignty, compliance and neighbouring industries.
Frequently asked questions
How does AI reduce food waste in production?
By making waste attributable and predictable. Adaptrix links production, quality and sales data, uses explainable attribution to show which lines, shifts, products or suppliers drive waste, and forecasts perishable demand with cross-validated forecasting models so you produce to demand. Autonomous alerts flag emerging waste drivers before they become write-offs.
Does Adaptrix satisfy the traceability requirements of Regulation (EC) 178/2002?
Your ERP and MES remain the legal system of record — the one-step-back, one-step-forward obligation of Article 18 is met by your records. Adaptrix makes those records queryable end-to-end, so a lot trace or audit answer takes minutes instead of days and gaps in the chain become visible before an inspector finds them.
Which systems does Adaptrix connect to?
ERP systems (SAP, Microsoft Dynamics, Sage and others), MES and production databases, LIMS and quality systems, POS and sales channels, plus spreadsheets and CSV exports. Connections are read-only; there is no rip-and-replace.
Do our recipes or supplier data ever leave our infrastructure?
No. Adaptrix runs its language models on self-hosted open models, hosted for you in its own EU infrastructure. Prompts, recipes, costings and supplier terms are never sent to US cloud AI services and are never used to train third-party models. That covers both GDPR and trade-secret exposure.
How accurate is perishable demand forecasting?
It depends on your history: with roughly two years of sales data per SKU, cross-validated statistical models capture seasonality, promotions and weekday patterns and typically beat manual planning noticeably. In a pilot we measure forecast error against your current baseline, so the improvement is verified on your data, not claimed.
What does Adaptrix cost for a food producer?
A fixed annual price with €0 per-token — no usage metering, so analysis is never rationed. The tier depends on data sources and users; see the pricing page for details and an indicative configuration.
See your waste drivers in your own data
A 30-minute demo on realistic food-industry data: waste attribution, perishable forecasting and a live lot trace.
Ask it why.
Bring a real question from your business and watch a live answer — reasoning, sources and math included — or model what it saves you first.