AI platform for Food & Beverage
Your R&D remembers
every recipe
Mafer turns your quality, formulation and regulatory records — specs, CoAs, trials, sensory panels — into model-ready intelligence, embedded in your daily workflows.
Recipe name
Dehydrated vegetable stock — reduced sodium
Raw materials
Composition
↕ Auto-order · Total 100.0%Tip: the filler auto-completes to 100% — every panel recomputes live on each dosage change.
Taste profile
Each accord is drawn relative to the strongest — recomputed on every dosage change.
Cost
€1.36 per kg
per portion · dosage 8 g
target €1.90 · SAP standard cost · EUR @ 1
Nutrition · per 100 g
EU 1169/2011 · label auto-generated
Agents
Years of specifications, trials, batch controls and market approvals become the foundation your teams — and your models — run on.
Quality & QC
Specifications, certificates of analysis, batch controls and non-conformities structured into one auditable quality system.
NPD & Reformulation
Historical trials, recipes and sensory feedback become reusable knowledge that shortens development and reformulation cycles.
Regulatory & Labeling
Ingredient rules, allergens, claims and market-specific requirements encoded into workflows that keep every label compliant.
Food companies run quality across spreadsheets, PDF certificates, ERP entries and lab notebooks. Answering "why did this batch deviate?" means hours of manual archaeology.
Mafer unifies specs, supplier documents, analytical results and batch records into structured, traceable data — so audits, deviations and supplier reviews take minutes, not days.
Cost pressure, ingredient substitutions, clean label, nutritional targets: every brief today restarts a cycle of trial and error your company has already paid for.
Models trained on your own history propose candidates that respect taste, process and compliance constraints — so your technologists iterate from a head start, not from scratch.
From ingredient and flavour houses to finished-product brands, these businesses share the same foundation: complex recipes, demanding quality standards and highly specialized data.
Quality Data Capture
Specs, CoAs & batch records
Full Traceability
From supplier to shelf
Predictive NPD
Models trained on your history
Market Compliance
Labeling & regulatory, always current
Very little of it becomes operational intelligence. The knowledge is there — it just doesn't compound:
Scattered Quality Data
Specs, CoAs and batch records live across spreadsheets, PDFs and inboxes.
Slow NPD Cycles
Every brief starts from scratch because past trials are not reusable.
Regulatory Drift
Labeling and market rules change faster than manual processes can follow.
Sensory Gap
Panel and consumer feedback never connects back to formulation data.
Eight weeks, on your own data. We start from plain exports, so there is nothing to integrate with your ERP, and we agree on the KPIs before the pilot begins.
Data audit
We map what you have — ERP records, Excel macros, instrument outputs, scanned notebooks — and tell you exactly what's usable. No cleanup required on your side.
Build
We build the proof on your own data — structuring it, automating the workflow, or training a model on your history. Whatever your case calls for, your data stays exclusively yours.
Validation
Your team tests it on your own recipes, against the KPIs agreed upfront — before any long-term commitment.
FAQ
Real questions from R&D, IT and quality teams across our conversations — answered straight.
No. Each client gets their own models, fine-tuned exclusively on their own data. Nothing is pooled across clients, and nothing you share with us ever improves anyone else's system. What remains after training is your model — raw data is never reused beyond it.
Wherever you decide. We deploy in the region each client determines, whether that is Southern Europe or any other location, and we work with all major cloud regions. Data lives on enterprise-grade infrastructure, encrypted in transit and at rest. For companies with stricter policies we deploy inside your own cloud environment, and on-premise for the strictest ones. Our security architecture documentation is available on request.
That's the starting point for almost every client. Every engagement begins with a data audit: we map what exists — ERP records, spreadsheets with macros, instrument outputs, even scanned notebooks — and tell you exactly what's usable before any commitment. You don't need to clean anything first; structuring messy technical data is precisely what Mafer is built for.
A typical pilot runs about eight weeks: two of data audit, four of building on your data, two of validation against KPIs we agree on upfront. It runs on plain exports, with no ERP integration to start, and asks around three hours per week from your team.
Less than you'd expect. We start from base models built for your domain and fine-tune them on your history, so even small datasets move the needle. Quality beats volume: complete iteration records — trials, failures, adjustments — teach a model more than thousands of final formulas alone.