Enterprise

One policy model across every plant in the group.

Multi-site beverage groups standardize on Brewira with a plant-edge fleet, shared model governance, custom recipe, product and tolerance models per site, SLAs and outcome-based components. Recipes and supplier data stay with each site.

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$650k – $8.5M ACVMulti-site fleetOn-prem or private cloud

run_scn_01 · agent graph · scenario 10 nodes · 1 approval gate
01 · orchestrator order.receive ✓ SUCCEEDED 02 · orchestrator twin.simulate ✓ SUCCEEDED 03 · brew_blend brew.blend ✓ SUCCEEDED 04 · ferment_yeast ferment.control ✓ SUCCEEDED 05 · filter_carbonate carbonate.dose ✓ SUCCEEDED 06 · fill_seal fill.seal ✓ SUCCEEDED 07 · defect_inspect inspect.line ✓ SUCCEEDED 08 · pasteurize_cip pasteurize.verify ✓ SUCCEEDED 09 · orchestrator approve.human ◆ APPROVAL 10 · quality_conf release.genealogy ✓ SUCCEEDED

Illustrative scenario: Plant run · one lager batch from brewhouse to can · brewhouse, cellar, filler, tunnel pasteurizer. Not a measured run.

Capabilities

What enterprise actually means here

The controls a food-safety-critical, multi-site beverage group expects, packaged from the start.

Fleet

Plant-edge fleet management

Edge appliances across sites with shared model governance, version routing, canary rollout and rollback.

Models

Custom recipe, product and tolerance models

Site-specific brand, package and process models trained on that site's outcomes, never on another customer's.

Access

SSO, role-based access, named approvers

On the roadmap for the 6 to 12 month window alongside SOC 2 Type II.

Records

Immutable audit logs and validation reports

Per model version, per site, exportable to the group quality system for food-safety teams.

Deployment

On-prem or hybrid

For producers protecting recipes, supplier data and food-safety records.

Commercial

SLAs and outcome components

Multi-year agreements with usage ramps and a share of measured yield, giveaway, water or energy improvement.

Run timeline

The same run record, at every site

Every Brewira run is an ordered, inspectable sequence. This is run_scn_01, an illustrative scenario: Plant run · one lager batch from brewhouse to can · brewhouse, cellar, filler, tunnel pasteurizer. Scenario complete · batch inside spec · one human approval at the pasteurizer.

run_scn_01 scenario · not measured SUCCEEDED
  1. 01 order.receive SUCCEEDED 0.8 s

    Plant Orchestrator · Pulled the recipe, the package spec, the HACCP plan with its pasteurization critical control point, the yeast lot record and the standing CIP window from the beverage MES and the lab system; locked the target envelope for the run.

  2. 02 twin.simulate SUCCEEDED 38 s

    Plant Orchestrator · Simulated 24 candidate brew, fermentation and carbonation plans on the Cuvera as-produced twin; ranked them on gravity margin, predicted finish time, CO2 target, PU margin, takt and CO2 and energy use, and discarded every candidate that thinned the pasteurization margin.

  3. 03 brew.blend SUCCEEDED 2 m 40 s

    Brew-and-Blend · Held wort gravity to recipe from the inline gravity analyzer and the brewhouse PLC, trimming the blend and utilization setpoints inside the recipe window rather than correcting after a spot lab check.

  4. 04 ferment.control SUCCEEDED 5 d 06 h

    Ferment-and-Yeast · Predicted the attenuation curve and finish time for the tank from inline gravity, dissolved oxygen and CO2, pH and temperature; held the temperature ramp and timed the crash inside the brewmaster-approved window; no stuck or runaway fermentation was flagged.

  5. 05 carbonate.dose SUCCEEDED 3 m 15 s

    Filter-and-Carbonate · Fused inline CO2, dissolved oxygen, turbidity, temperature and pressure; held carbonation to the package target with the minimum CO2 and timed the filter backwash from the predicted loading instead of a fixed schedule.

  6. 06 fill.seal SUCCEEDED continuous

    Fill-and-Seal · Adjusted fill valves toward the target level inside the approved window using drift feedback from inspection, and ran seam checks on the seamer; the filler corrected upstream instead of rejecting downstream.

  7. 07 inspect.line SUCCEEDED continuous

    Defect-and-Inspect · 16 camera streams at the line edge: fill level, seam and cap, label and date code, foreign body and container checks on every can; three low-fill rejects were attributed to one filler valve and Fill-and-Seal corrected it.

  8. 08 pasteurize.verify SUCCEEDED continuous

    Pasteurize-and-CIP · Held the tunnel pasteurizer on the validated PU profile at the lowest zone energy inside the envelope; every critical control point reading was written to the audit log against the HACCP plan and the CIP release checks were armed.

  9. 09 approve.human APPROVAL 1 m 52 s

    Plant Orchestrator · The lowest-energy candidate wanted to move the pasteurizer CIP into a window that overlapped the next brand's start. Held for the shift quality manager, who kept the validated PU profile untouched and approved the CIP move with a tighter release check.

  10. 10 release.genealogy SUCCEEDED 1 m 05 s

    Quality-and-Conformance · Batch released: gravity and attenuation curves, yeast lot, CO2 and clarity, fill and seal outcomes, inspection rejects, PU readings, CIP release and every human decision written to the batch genealogy and checked against spec.

Autonomy

Four stages, set per loop

A plant does not go from manual to bounded control in one step. Brewira makes the stage explicit per loop, auditable and reversible at any time, and some decisions never leave the person.

Autonomy stages and the human role at each
StageWhat the agent doesWhat the person doesWhen
ShadowPredicts gravity, attenuation, carbonation, fill and seal faults, contamination and takt; writes nothingRuns the plant as today; compares predictions to lab, QA and PLC outcomesFirst phase with every design partner
AssistRecommends bounded brew, fermentation, carbonation, fill and seal, pasteurization and CIP moves with the evidenceA brewmaster, process engineer or quality manager approves or rejects each oneAfter accuracy is proven against the baseline
BoundedWrites low-risk filling, carbonation and inspection setpoints inside documented recipe, quality, food-safety, equipment and rollback limitsApproves anything above the limits; reviews the shift recordAfter the food-safety and ROI gates agreed up front
ExceptionsEscalates anything outside its envelope, CCP-adjacent moves and release decisionsAlways decides these; the agent never doesPermanent
Rollout

How a group rollout runs

The expansion path: one line with a hard ROI metric; one plant with multiple agents; a multi-site fleet with shared governance; then group benchmarks.

  1. One line, one metric. A design-partner pilot on the line with the largest exposure, baselined in shadow mode.
  2. One plant, many agents. The Plant tier: adjacent agents, the Cuvera twin, whole-plant genealogy.
  3. Many plants, shared governance. The plant-edge fleet with model versioning, validation status per site and group autonomy policy.
  4. Benchmarks. Yield, loss, giveaway, water, energy and contamination benchmarks by beverage type as premium data products, with site data kept tenant-scoped and recipes never exposed.
Tool calls

Auditable at group level

Every tool invocation, argument and result is written to an immutable, human-readable log, and every reasoning step is expandable. Nothing about a run is hidden from the plant. The log below is the scenario run, not a measured one.

tool-call stream · run_scn_01
  1. 04:50:02mes.read_order({ batch: "L-0931", brand: "LAGER-33", package: "CAN-330" })
  2. 04:50:02ok recipe locked · HACCP plan v6 · CCP: tunnel PU 15–20
  3. 04:50:03lab.read_results({ yeast_lot: "Y-2207", test: "viability" })
  4. 04:50:03ok viability inside window · lot accepted for pitching
  5. 04:50:04twin.simulate({ candidates: 24, horizon: "batch" })
  6. 04:50:42ok best plan #7 · PU margin held · lowest CO2 and energy per hl
  7. 04:50:43policy.evaluate({ plan: 7, stage: "bounded" })
  8. 04:50:43ok 7 writes permitted · 1 write requires human approval
  9. 04:50:44plc.write_setpoint({ tag: "BH1.BLEND_RATIO", basis: "gravity+recipe" })
  10. 04:53:24ok wort gravity on recipe · utilization held
  11. 05:10:00ferment.predict_curve({ tank: "FV-12", lot: "Y-2207" })
  12. 05:10:00ok attenuation curve predicted · finish day 5 · crash timed
  13. 05:10:01plc.write_setpoint({ tag: "FV12.TEMP_RAMP", window: "brewmaster_approved" })
  14. 05:10:01ok ramp applied · no stuck or runaway ferment flagged
  15. 06:02:10plc.write_setpoint({ tag: "CARB1.CO2_DOSE", basis: "co2+do+turbidity" })
  16. 06:05:25ok CO2 on package target · clarity inside spec · backwash timed
  17. 06:05:26vision.stream({ cameras: 16, models: ["fill_level", "seam_cap", "label_ocr", "foreign_body"] })
  18. 06:31:48reject: low fill · can 20417 · attributed to filler valve 14 drift
  19. 06:31:49defect.attribute({ event: "low_fill", cause: "filler.valve_14" })
  20. 06:31:49ok fill_seal notified · valve 14 trimmed inside window · two more rejects, then clean
  21. 06:31:50plc.verify_pu({ tag: "TUN1.ZONES", profile: "validated" })
  22. 06:31:50ok PU inside profile · readings → audit log
  23. 06:31:52approval.request({ action: "cip.window", reason: "overlaps next brand start" })
  24. 06:33:44ok approved by the shift quality manager · PU profile untouched · tighter release check
  25. 09:12:30mes.release_batch({ batch: "L-0931", genealogy: "full" })
  26. 09:13:35ok batch released · scenario complete

Reasoning trace

Goal, plan, thought, action, observation, exactly as the orchestrator would record it.

GoalBrew batch L-0931 to recipe gravity, ferment it to target atte…

Brew batch L-0931 to recipe gravity, ferment it to target attenuation, carbonate and fill it to spec at line speed, pasteurize it on the validated PU profile and release it with full genealogy.

PlanSimulate the whole batch on the twin first. Lead with gravity …

Simulate the whole batch on the twin first. Lead with gravity so the cellar gets the right wort and the filler gets the right CO2. Verify the pasteurization critical control point continuously. Let the filler chase target level only inside the approved window; hold anything beyond the envelope for a human.

ThoughtThe standing practice over-fills to avoid low fills and over-g…

The standing practice over-fills to avoid low fills and over-gasses to avoid flat product. With continuous fill-level estimation and inline CO2 the filler and the carbonator can sit at target. The saving is giveaway, not safety margin: the pasteurization CCP is never a candidate for optimization.

Actiontwin.simulate(candidates=24) → plan #7: gravity on recipe, fin…

twin.simulate(candidates=24) → plan #7: gravity on recipe, finish day 5, CO2 at package target, PU margin unchanged, lowest predicted CO2 and energy per hectoliter.

ObservationPlan #7 wants the pasteurizer CIP in a window that overlaps th…

Plan #7 wants the pasteurizer CIP in a window that overlaps the next brand's start. The policy engine routes that single move to the shift quality manager and permits the other seven writes.

ActionExecute plan #7 at the bounded stage: brewhouse blend, tank ra…

Execute plan #7 at the bounded stage: brewhouse blend, tank ramp, CO2 dosing and fill-valve writes proceed; PU is verified continuously; the CIP move waits.

ObservationApproval granted at 06:33:44 with the PU profile untouched and…

Approval granted at 06:33:44 with the PU profile untouched and a tighter CIP release check. Three low-fill rejects were attributed to filler valve 14 and corrected by Fill-and-Seal inside the approved window.

OutcomeScenario complete. The batch is released with gravity and atte…

Scenario complete. The batch is released with gravity and attenuation curves, yeast lot, CO2 and clarity, fill and seal outcomes, PU readings, CIP release and the human decision in the genealogy. No measured plant result is claimed; this is the run the platform is designed to execute.

Governance

Autonomy needs an owner

Group policy

The autonomy stage per loop, the tag allow-lists, the rate and magnitude limits and the approval chains are declared once at group level and overridden per site where the site's HACCP plan requires it.

Site ownership

Each site's quality and food-safety manager remains the approver for critical control points, CIP release and batch release. Brewira records the decision; it does not take it.

Guardrails

An agent that can move a setpoint needs a leash

Brewira writes to production equipment in a food plant. Every capability is scoped, every write is policy-checked, every output is cited, and every action is written to an append-only audit log the plant owns.

  • Bounded action space. Each agent can only write to an explicit tag allow-list, inside per-tag rate and magnitude limits, at the autonomy stage the plant has set.
  • Critical control points are read, never written. Pasteurization units, CIP release checks and batch release decisions stay with the HACCP plan and the people who own it.
  • Policy engine before every write. Autonomy stage, interlock state, product, shift and operator presence are evaluated before a setpoint moves.
  • Grounded and cited. Every recommendation carries a citation to the recipe, spec or procedure it relied on. Retrieval is tenant-isolated and permission-aware.
  • Immutable audit log. Append-only, exportable and retained on the plant's own storage, aligned to HACCP, FSMA, FSSC 22000 and BRCGS record-keeping.
  • Hard fallback. If the edge node, the network or a model stops, the plant keeps running on its existing PLC and SCADA control and interlocks.
  • Tenant and IP isolation. Recipes, supplier data and tolerance models never cross a customer boundary. On-prem deployment available.

Assurance posture

ItemScopeStatus
SOC 2 Type ICloud control plane QUEUED Roadmap, first 6 months
SOC 2 Type IICloud control plane QUEUED Roadmap, 6 to 12 months
HACCP · FSMA · FSSC 22000 · BRCGSGrounding and record-keeping RUNNING Design basis for retrieval and the audit log
Per-tenant isolationData, memory, models RUNNING Design rule
On-prem deploymentRecipe-sensitive producers RUNNING Design option

Brewira supports your food-safety records. It is not a certification and it does not replace your HACCP plan.

Read the security overview

Multi-agent handoff

Agents negotiate, they do not collide

Two agents will want the same actuator. The orchestrator arbitrates on the run goal, with food safety above everything, and the handoff is logged like any other step.

Contested move: tunnel pasteurizer belt speed

  1. 01yield_takt.request(belt +5%) SUCCEEDED0.2 s

    Yield-and-Takt wants more belt speed through the tunnel pasteurizer so the filler is not held back and the shift meets takt.

  2. 02pasteurize_cip.request(belt hold) SUCCEEDED0.2 s

    Pasteurize-and-CIP requires the belt speed that keeps every container inside the validated PU profile. That is the HACCP critical control point.

  3. 03orchestrator.arbitrate SUCCEEDED0.4 s

    Food safety outranks takt under every run goal. The critical control point wins the actuator; the request for more speed is logged with its score and the reason it lost.

  4. 04yield_takt.handoff(resequenced) SUCCEEDED90 s

    Yield-and-Takt recovers the schedule by pulling the next changeover earlier and shifting the CIP window instead. Takt is met without touching the CCP.

Arbitration rules

  • Run goal first. Every request is scored against the declared goal, not against the requesting agent's local objective.
  • Food safety outranks everything. A critical control point is never an optimization variable. An under-pasteurized or contaminated batch is a recall; a takt miss is a schedule.
  • Time-boxed ownership. An agent holds a contested actuator for a bounded window, then must re-justify.
  • Everything is logged. The losing request, the score and the reason all appear in the run record.
  • Deadlocks escalate to a human rather than resolving by timeout.

See the agent roster

Design targets

Group-scale design targets

The numbers Brewira is engineered against, from the GPU utilization plan.

<100 ms edge inference for a reject decision at line speed
<250 ms drift alert to the fill-and-seal agent
8–24 camera feeds per high-speed filling or packaging line
60–240 FPS aggregate frames processed per line, depending on container speed
20–60 deployed model versions per enterprise tenant, with canary rollout and rollback
100k–1M labeled synthetic rare-defect variants per design-partner phase

Design targets from the GPU utilization plan, all marked aspirational in the architecture. Nothing on this page is a measured plant result; measurements start when the first design-partner line runs in shadow mode.

Integrations

It speaks plant, not cloud

Brewira reads and writes through the systems already on the floor. No parallel historian, no new HMI, no rip-and-replace. Connectors are built against each design partner's stack first; long-tail integrations are out of scope for the first release.

Brewhouse and fermentation

PLC and SCADA of brewhouse, blending and syrup systems, fermentation tanks and yeast handling

Setpoint reads, guarded writes, interlocks untouched

Filtration and carbonation

Filtration and carbonation skids and their inline CO2, dissolved-oxygen and turbidity analyzers

Continuous carbonation and clarity state

Filler, seamer, capper

High-speed filler, seamer and capper controls

Telemetry in; fill-valve and seam settings inside approved windows

Pasteurizer and CIP

Tunnel and flash pasteurizers, CIP skids and hygiene sensors

PU readings verified and logged; CIP release checks

Inspection

Multi-camera stations for fill level, seal and cap, label, foreign body and container defects

Frames, defect events, reject commands

Beverage MES and lab

Orders, recipes, product specs, batch genealogy, LIMS results

Targets in, release records out

Energy, water, robots

Plant and asset meters; Isaac-driven pack, case and palletizing cells

Hard constraints for scheduling; bounded handling

Identity (planned)

SSO and role-based access; SOC 2 on the roadmap

Named approvers, scoped roles

See all integrations

From the plant floor

Who this is built for

The three people in a beverage plant whose week changes when the process runs itself, and what each of them needs from Brewira.

Economic buyer

Plant or Operations Director

Owns production rate, quality, loss, giveaway and yield, water and energy, and food safety. Wants a plant that holds spec at higher rate with fewer interventions, and a number that justifies the spend.

Champion

Brewmaster or Process Engineer

Owns recipes, brewhouse and blend, fermentation and carbonation process windows and yield. Approves and corrects the agents in assist mode; those corrections train the models.

Approver

Quality or Food-Safety Manager

Owns product quality and safety under HACCP, FSMA, FSSC 22000 and BRCGS, contamination and fill and seal conformance, and batch genealogy. Needs every action grounded, cited and written to an immutable record.

IT/OT and sustainability leads approve the deployment. There are no customer quotes on this site yet; design partners will speak for themselves when they choose to.

FAQ

Straight answers

The questions plant directors, brewmasters and quality managers ask in the first meeting.

Only at the autonomy stage your plant has set, and only to an explicit allow-list of low-risk loops inside documented limits. Every design partner starts in shadow mode, where Brewira predicts and writes nothing. Assist mode follows, where a brewmaster or process engineer approves each recommendation. Bounded autonomy on filling, carbonation and inspection loops comes after the food-safety and ROI gates agreed up front.

Get started

Standardize the way your group runs its plants

Start at one site. Expand on the number.

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