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DFX: AI-Native MES Software for Food and Beverage Manufacturing

DFX is built for AI from the ground up to run directly on the live system of record so it can act on what is happening now.

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What makes an MES AI-native

Most MES add AI later, working on a copy of the production data. An AI-native MES such as the DFX runs AI on the live record itself in place.

Traditional MES
DFX: AI-Native MES
Deployment
Installed on-premise, one server per site
Cloud-native. Deploy once and run every plant on it
Data foundation
A copy, exported to a separate tool
The live production record in place
Data freshness
Stale the moment it is copied
Always the real state of the floor
AI capability
Reports on what already happened
Acts on what is happening now
Scaling across plants
Each plant a separate build, flat return per site
Every plant added makes the models and agents smarter for the rest

DFX is the record AI runs on, not a layer that sits on top of one.

One live record for food and beverage production lines

Every food and beverage plant runs the same core operations, from incoming material checks through in-process quality, line performance, and packaging. DFX captures each of them once, on the floor, and ties them to the run, so production, quality, and performance live in one record instead of seven disconnected systems.

Pre-process checks

setup & incoming checklist

›

In-process checks

quality logbook

›

Line performance

OEE spreadsheet

›

Packaging & dispatch

dispatch / WMS

›

ERP reconciliation

keyed into ERP

THROUGHOUT
THE RUN
Maintenance → maintenance log
Energy & consumables → utilities register
Seven domains, unified by DFX.
▼ ▼ ▼ ▼ ▼
DFX Data Record · tied to the run

DFX puts an agent on the record to capture problems before they surface

A dashboard waits for you to look, ask the right question, and catch the problem in time. An agent reads the live record continuously and tells you what needs attention before you go looking.

A dashboard
A DFX agent
You have to know what to ask
Brings the problem to you, unprompted
Shows only what you thought to check
Surfaces the losses you would never have gone looking for
Only as good as who is watching, and when
Nothing slips past on a busy shift, across every line and plant
Tells you after it already cost you
Flags it while there is still time to act

From a single run to the whole operation

Hold a batch before it drifts
An agent watches the run, catches a batch trending out of spec, and flags it for hold before it moves to the next stage.
Rebalance in the moment across the lines
An agent sees one line falling behind and recommends how to rebalance the others the moment it happens.
Plan against order book
An agent reads the open orders and recommends how to sequence them against the capacity the floor can actually deliver this week.

DFX agents take on the constant supervision, so operators, supervisors, and planners are freed up for the decisions that need human judgment and strategic thinking.

Proven across live food and beverage deployments

200+

lines connected

8%

average OEE improvement

170+

plants live

XXM+

cases traced annually

Case study snapshot

Pernod Ricard: Scaling operational intelligence across 30 facilities

Pernod Ricard: Scaling operational intelligence across 30 facilities

Altizon’s DFX Platform unified Pernod Ricard’s production, quality, and sustainability data by replacing fragmented, paper-based…

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Large Beverages Major: Standardizing performance across multi-OEM bottling lines

Large Beverages Major: Standardizing performance across multi-OEM bottling lines

Altizon’s DFX Platform helped large beverages major connect multi-OEM bottling lines and utilities into a…

Read more

Frequently asked questions (FAQs)

An AI-native MES is a manufacturing execution system built for AI from the start. The live production record that runs the plant is the same record the AI runs on, in place, so there is no separate copy to build on. DFX is an AI-native MES for food and beverage.
An MES is AI-native when it is built for AI from the start, not adapted later. The record that runs production is the record models and agents run on, so they act on what is actually happening on the floor, not on a stale copy. Because that record is reconciled and tied to each run, the AI can be trusted to act on it.
An AI-enabled MES records production, then teams copy that data out into a separate tool and build AI on the copy. That copy is stale the moment it lands and is cut off from the live run. An AI-native MES runs AI on the live record itself, so the AI always sees the real state of the floor and can act on it.
You can, but the usual route is to copy the data out to a separate platform first. That copy is stale the moment it lands and is detached from the live operation, so the AI can report on the past but cannot act in the present. An AI-native MES removes the copy step by running AI on the live record.
Agentic AI uses software agents that watch the live operation and surface what needs attention, rather than waiting to be asked. An agent can flag a recurring minor stop before it becomes the shift's biggest loss, or recommend how to rebalance lines when one falls behind. The agent takes on the constant watching, so teams act sooner.
A dashboard is pull: you decide what to look at, ask the question, and read the answer. An agent is push: it watches the whole record continuously and surfaces what needs attention, including things you would not have thought to check. Analytics report on what already happened; an agent acts on what is happening now.
In practice, yes. An agent is only as good as the data it can see and the actions it can trust, and that requires a record that pulls machine and human data together, reconciles it, and ties it to the batch. The AI runs on that record, and the record has to be built first.
No. Agents take on the constant monitoring and routine response, so operators, supervisors, and planners are freed for the decisions that need human judgment. The goal is to remove busywork, not people.
Yes. Because every plant runs on the same reconciled record, the data from each one makes the models and agents better for the rest. A copy-out approach cannot do this: each plant is a separate integration, so the return stays flat per site.
Yes. DFX is an AI-native MES built for food and beverage manufacturing. It brings pre-process and in-process checks, line performance, packaging, maintenance, energy, and ERP reconciliation into one live record tied to each run, then runs predictive models and agents on that record. It is in production across food and beverage plants today.

Ready to put AI on a live record of your floor?

Start with the lines that matter most and put AI on a live record of your floor, not a copy of it.

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