FoundryNet / OEMs / Food & beverage process

PROCESS / BATCH · CANONICAL DATA MODEL

Food & beverage process canonical data model: connect your Food & beverage process equipment to any AI agent

2,461 confirmed mappings·12 protocols·96% field coverage

Forge turns raw Food & beverage process tags into one clean, governed schema your AI agent already understands. One MCP call, no per-line integration project.

Try it free: 3 machines, no credit card → See it work →

Paste your Food & beverage process data and see it normalized in 30 seconds. No POC required.

Read-only. Forge reads your Food & beverage process data through standard industrial protocols. Read-only. Your equipment is never at risk.

The problem

Why Food & beverage process data is hard to integrate

F&B lines mix CIP state, flow, temperature and fill counts across PLCs from a dozen skid vendors, so line-level analytics stall on tag mapping before they ever start.

Typical Food & beverage process equipment communicates over OPC UA, Modbus TCP, MQTT Sparkplug B, BACnet/IP. Each firmware revision, model line and integrator names the same physical quantity differently, so every AI or analytics project pays the integration tax again, the tax that cancels 40% of industrial AI deployments before they ship.

The solution

One universal schema for every Food & beverage process line

Forge resolves Food & beverage process telemetry into Forge's canonical field set, the same 1,027-field canonical schema (366 resolvable from vendor tags today), used across all 47 vendor packs. Point Forge at the line, pass oem: "food", and spindle speed is spindle_speed_rpm whether it came from a Food & beverage process controller or anything else on the floor.

OPC UAModbus TCPMQTT Sparkplug BBACnet/IP

Vertical pack · 2,461 curated mappings

96%Field coverage

10Canonical process / batch fields

3,444Corpus mappings

Field coverage

What Forge resolves for Food & beverage process

Confirmed canonical fields your agent gets from Food & beverage process lines, drawn from Forge's 3,444-mapping corpus:

process.batch_idprocess.phase_stateprocess.reactor.temp_cprocess.reactor.pressure_barprocess.jacket.temp_cprocess.agitator_rpmprocess.flow_rateprocess.phprocess.level_pctprocess.cip_state

Sample normalization

Raw tag in		Canonical field out	Meaning
CIP_STATE: "RINSE"	→	process.cip_state: "RINSE"	clean-in-place state
FLOW_LPM: 210	→	process.flow_rate: 210	product flow
TANK_LVL: 68	→	process.level_pct: 68	tank level %
PROD_TEMP: 4.2	→	process.reactor.temp_c: 4.2	product temperature

30-second deployment

Add Food & beverage process to your agent with one call

No SDK, no per-tag mapping, no historian project. Connect the MCP server and normalize live Food & beverage process data:

claude mcp add --transport http forge https://mcp.foundrynet.io/mcp --header 'Authorization: Bearer YOUR_API_KEY'

# normalize raw Food & beverage process telemetry into the universal schema

curl -s https://forge.foundrynet.io/v1/normalize \

-H 'Content-Type: application/json' \

-d '{"data": {"CIP_STATE": "RINSE", "FLOW_LPM": 210, "TANK_LVL": 68}, "oem": "food"}'

{"process.cip_state": "RINSE", "process.flow_rate": 210, "process.level_pct": 68, "coverage": "100%", "confidence": 0.97}

Unknown tags never get force-mapped. Fields below the confidence floor abstain rather than guess, so your agent never acts on a bad reading.

Start free: Forge API, 3 machines → See the full demo →

Where Food & beverage process fits

Protocols
OPC UA Modbus TCP MQTT Sparkplug B BACnet/IP

Vertical
process / batch

Other process / batch vendors
Chemical process Pharma process (GMP)

Same protocols, other industries
ABB Robotics DMG Mori Fanuc Heidenhain

Also searched as food, beverage, food and beverage, food-bev, cip, dairy