Physical AI · Brewing and beverage autonomy

The plant runs itself. You decide how far.

Brewira is an agent operating system for brewing and beverage manufacturing. Eleven agents control brewhouse and blend, fermentation and yeast, filtration and carbonation, high-speed filling and sealing, pasteurization and CIP, inspection and handling, watched by line-edge vision and inline analyzers, rehearsed on an as-produced batch twin, and bounded by an autonomy policy you set per loop.

Book a line review See the platform

QUEUED design stageScenario run shown, not measuredFirst design partners wanted

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.

Built for

Beer and brewing Soft drinks Bottled and sparkling water Juice Energy and functional RTD, dairy-alt and co-packers

Beverage types, not customers. Brewira has no plant connected yet and is recruiting its first design partners.

Run timeline

One scenario run, step by step

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.

Tool calls

The agent shows its work

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.

How it works

A goal becomes a plan becomes a run

Nothing about a Brewira run is implicit. The goal is declared, the plan is rehearsed on the twin, each step is typed, and the outcome is written to the batch genealogy.

Active path

The orchestrator plans, the agents act

A run starts as a goal, becomes a plan, and executes as a graph of typed steps. The active path is always visible, always logged, always reversible.

RUNNING APPROVAL SUCCEEDED
Perceive Cameras, inline analyzers, lab data, PLC and SCADA, meters
Predict Gravity, attenuation, carbonation, fill and seal, contamination, shelf life, takt
Act Bounded setpoint and recipe moves, with a person above the threshold
Record Audit log and batch genealogy, retrained from every correction
Human in the loop

Autonomy is a dial, not a switch

Shadow, assist, bounded, exceptions. Each plant sets the stage per loop, and anything above the threshold, every critical control point and every release decision waits for a named person.

Agent roster

Eleven agents and an orchestrator

Each agent owns a stage of the plant, a bounded tool set and a measured outcome. They negotiate for shared actuators through the orchestrator, never directly. Five ship as products; the rest arrive with the Plant tier, and the knowledge agent has no write tools at all.

agent.brew_blend

Brew-and-Blend

Brewhouse, blending, syrup, gravity, recipe

Reads inline gravity, flow and temperature against the recipe and holds mash or blend, syrup ratio and utilization at target, so wort and blend leave the brewhouse on gravity and on flavor spec instead of drifting between spot lab checks.

analyzer.read_gravityplc.read_brewhouseplc.write_setpoint(blend)

Design scope: gravity and recipe on target, utilization held

Ships in: Plant tier

agent.ferment_yeast

Ferment-and-Yeast

Fermentation, yeast and culture, attenuation, flavor profile

Fuses inline gravity, dissolved oxygen and CO2, pH, temperature and pressure with a physics-informed fermentation model to predict each tank's attenuation curve, flavor profile and finish time, then holds temperature ramps, pressure and pitching, cropping and harvest inside brewmaster-approved windows.

analyzer.read_tankferment.predict_curveplc.write_setpoint(tank.temp)

Design scope: attenuation and flavor on target, less tank time

Ships in: Fermix

agent.filter_carbonate

Filter-and-Carbonate

Filtration, clarity, carbonation with CO2 or nitro

Fuses inline CO2 and dissolved oxygen, turbidity, temperature, pressure and flow to predict in-line carbonation and clarity, then controls dosing, pressure and filtration inside spec windows to hold CO2 and clarity to target with the least CO2 wasted.

analyzer.read_co2_clarityfilter.predict_loadingplc.write_setpoint(co2.dose)

Design scope: CO2 and clarity to spec at minimum CO2 waste

Ships in: Carbyn

agent.fill_seal

Fill-and-Seal

High-speed filling, fill level, seaming, capping, sealing

Takes drift signals from inspection and adjusts fill valves, carbonation pressure at the filler, seam checks and capper settings inside approved windows, so the filler corrects toward target level instead of over-filling to avoid low fills.

filler.read_telemetryplc.write_setpoint(fill.valve)seamer.check

Design scope: target fill level with minimal giveaway, no leakers

Ships in: Sealix

agent.pasteurize_cip

Pasteurize-and-CIP

Tunnel and flash pasteurization, PU, CIP, hygiene

Monitors and controls tunnel and flash pasteurization to the target pasteurization units at minimum energy and thermal flavor impact, verifies CIP hygiene from sensor and analyzer signals, writes every critical control point reading to the audit log and holds release until the evidence is complete.

plc.verify_pu(zone)cip.verify_releaseaudit.write

Design scope: target PU at minimum energy, CIP release proven

Ships in: Pastura

agent.defect_inspect

Defect-and-Inspect

Fill level, seal and cap, label, foreign body, clarity, container faults

Runs multi-camera vision at the line edge for fill-level estimation, seam and cap integrity, label placement and OCR, clarity, container defects and foreign bodies, rejects off-spec containers and attributes each defect back to the filler, seamer or upstream state that caused it.

vision.stream(cams)reject.actuatedefect.attribute

Design target: sub-100 ms reject decisions, sub-250 ms drift alerts

Ships in: Sealix

agent.quality_shelflife

Quality-and-Shelflife

Flavor, clarity, carbonation, shelf life

Predicts shelf life and finished-product quality from gravity, attenuation, carbonation, PU margin and inspection outcomes, and proposes the recipe and process moves that protect both before the batch is released.

shelf.predictspec.checkrecipe.propose

Design scope: quality and shelf life predicted before release

Ships in: Plant tier

agent.yield_takt

Yield-and-Takt

Yield, loss, water, energy, line balancing

Prices every candidate move in hectoliters, kilograms of CO2, kilowatt-hours and cubic meters of water, sequences brews, tanks, changeovers and CIP cycles, and balances the moving line so takt is met without starving the filler or the pasteurizer.

cuopt.sequencewater.budgetenergy.budget

Design scope: yield up, loss, water and energy down

Ships in: Plant tier

agent.robot_handling

Robot-and-Handling

Pack, case and palletizing handling

Drives pack, case and palletizing handling of containers, packs and pallets with perception and motion policies validated in simulation first, inside safety zones, with audited actions and operator approval. It does not claim plant-wide robotic labor.

isaac.policy(pack)robot.move(bounded)zone.check

Design scope: constrained handling, safety zones, approvals

Ships in: Plant tier

agent.quality_conf

Quality-and-Conformance

Right-first-time, non-conformance, batch genealogy, traceability

Builds the batch genealogy record, gravity and attenuation curves, CO2 and clarity, fill and seal outcomes, PU readings, CIP release checks and every human decision, and gates release against product spec and the plant's food-safety procedures.

mes.release_batchgenealogy.writeaudit.write

Design scope: complete, immutable release records

Ships in: Plant tier

agent.bev_knowledge

Beverage-Knowledge

Grounded process and food-safety questions

Answers brewers', process engineers' and quality managers' questions over recipes, brewing, fermentation and carbonation specs, HACCP, FSMA, FSSC 22000 and BRCGS procedures and CIP records, with a citation on every answer. It has no write tools and cannot act on the plant.

rag.retrieve(cited)answer.compose

Design rule: every answer cites a source; no write tools

Ships in: Every tier

agent.orchestrator · coordinates all eleven

Plant Orchestrator

Planning, arbitration, human approval, twin rehearsal

Plans the run, rehearses high-impact moves on the Cuvera twin, arbitrates between agents that want the same actuator, enforces the autonomy stage per loop and routes anything above the site threshold to a named human. Grounds its reasoning in the plant's recipes, HACCP plan and CIP procedures through cited retrieval.

plan.composepolicy.evaluateapproval.requesttwin.simulate

Design rule: every write policy-checked, every output cited

Ships in: Every tier

Where it pays

Four loops, four baselines

Brewira is not a dashboard. Each agent closes a loop that a plant already measures in hectoliters, containers, kilograms of CO2, kilowatt-hours and rejects. No result is claimed here; the baseline is what a pilot measures first.

Giveaway

Fill giveaway and low fills on a filling line

Fillers over-fill to avoid low fills, so every container carries giveaway. Vision that feeds the filler lets the fill sit at target instead.

  • Ships in Sealix
  • Baseline: Fill giveaway per container and per shift; low-fill and leaker rejects by attributed cause
  • Shadow mode first; writes only after the agreed gates
Sealix QUEUED
What is measuredWhere the number comes from
Fill giveaway per container and per shiftYour lab, meters and QA records
Baseline periodShadow mode, before any write
ResultMeasured when the pilot runs
Attenuation

Attenuation variance and tank time

The highest-variance step in the plant, managed by hand from spot gravity readings. The curve is predicted and held; the craft is captured as a model.

  • Ships in Fermix
  • Baseline: Attenuation variance against target, tank time, downgraded batches per strain and tank
  • Shadow mode first; writes only after the agreed gates
Fermix QUEUED
What is measuredWhere the number comes from
Attenuation variance against targetYour lab, meters and QA records
Baseline periodShadow mode, before any write
ResultMeasured when the pilot runs
CO2 and clarity

CO2 use and clarity rejects on carbonation

Fixed dosing corrected after spot checks over-gasses product and spends CO2 blindly. Inline fusion holds CO2 and clarity to spec with the minimum gas.

  • Ships in Carbyn
  • Baseline: CO2 consumed per batch, off-spec and clarity rejects, filter changes
  • Shadow mode first; writes only after the agreed gates
Carbyn QUEUED
What is measuredWhere the number comes from
CO2 consumed per batchYour lab, meters and QA records
Baseline periodShadow mode, before any write
ResultMeasured when the pilot runs
PU and energy

Pasteurization and CIP at minimum water and energy

Fixed cycles over-process to stay safe. The PU profile is held and logged; the energy below it is the lever, and the CCP is never the variable.

  • Ships in Pastura
  • Baseline: Energy and water per hectoliter on pasteurization and CIP, PU margin held, audit-prep time
  • Shadow mode first; writes only after the agreed gates
Pastura QUEUED
What is measuredWhere the number comes from
Energy and water per hectoliter on pasteurization and CIPYour lab, meters and QA records
Baseline periodShadow mode, before any write
ResultMeasured when the pilot runs
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

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
Design targets

Design targets, not results

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.

Use cases

Where plants would start

Brewira is recruiting three to five design partners for the first cohort. These are the beverage types the products were designed around and where each would start.

Beer and brewing QUEUED

Beer and brewing

Brewhouse to can at scale: gravity, attenuation and fill. Starting wedge: Fermix on one cellar or Sealix on one filler.

Soft drinks QUEUED

Soft drinks

Carbonation and high-speed filling across proliferating SKUs. Starting wedge: Carbyn on a carbonation skid, Sealix on the filler.

Bottled and sparkling water QUEUED

Bottled and sparkling water

Fill level, cap and label at the fastest line speeds. Starting wedge: Sealix.

Juice QUEUED

Juice

Pasteurization, stability and fill. Starting wedge: Pastura on a pasteurizer, with Sealix on the filler.

Energy and functional QUEUED

Energy and functional

Launch cadence and recipe changes. Starting wedge: Cuvera for new-SKU planning, Carbyn and Sealix on the line.

RTD, dairy-alt and co-packers QUEUED

RTD, dairy-alt and co-packers

Many brands, many packages, one line. Starting wedge: Sealix, with Pastura where the product is pasteurized.

Accelerated computing

Physical AI, at the plant edge

Lines fill tens of thousands of containers an hour, so perception has to be local and fast. Brewira runs GPU inference at the line edge and keeps training, simulation and optimization in the cloud, in a private cloud or on-prem. Items marked planned are on the roadmap, not running.

Jetson Orin / Thor · DeepStream · TensorRT · Holoscan

Edge perception

8 to 24 camera feeds per line through DeepStream pipelines and TensorRT detectors, segmentation, OCR and fill-level models; Holoscan synchronizes cameras with gravity, CO2 and clarity analyzers and filler and pasteurizer telemetry. Design target: sub-100 ms reject decisions.

Triton · NIM

Model serving

Vision, time-series, anomaly, process and food-safety reasoning models behind one orchestrator, with version routing by brand, package and line. Design target: 20 to 60 model versions per enterprise tenant.

DGX / HGX · NeMo

Training (planned)

Line vision, time-series forecasters, anomaly models and NeMo-based beverage reasoning fine-tuned from labeled batch outcomes, brewmaster corrections, lab results and release decisions. Design target: weekly retraining for wedge models, monthly for validated process models.

Omniverse · Modulus · OVX

Digital twin (planned)

The Cuvera as-produced line twin: CUDA-accelerated fermentation, carbonation, mixing and pasteurization heat simulation run before the batch, for new SKU setup and batch planning when a trial is expensive.

Cosmos · Omniverse Replicator

Synthetic data (planned)

Rare leaker, low-fill, overfill, cap-skew, seam, label-shift, condensation, glare and foreign-body scenarios generated with domain randomization and validated against real plant events before use.

cuOpt

Optimization

Brew and fill schedules, changeovers, CIP cycles, water and energy allocation and takt balancing under line, tank, product and sanitation constraints, recomputed on the GPU when the plant is disrupted.

RAPIDS

Data engineering

Image, time-series and batch-genealogy ETL for feature generation, quality correlation and cross-plant benchmarks on the GPU.

Isaac · Jetson

Robotic handling

Pack, case and palletizing handling, with perception and motion policies built and validated in simulation before they move a pallet.

Developers

Every action is a record

There is no SDK to download yet. What design partners get is the integration surface: connectors, an autonomy policy declared per loop, and an audit record for every reading, recommendation, write and approval. This is the shape of one record, illustrative.

What the surface gives you

  • Connectors to PLC and SCADA, inline analyzers, lab systems, MES, cameras and meters, with declared allow-lists and limits
  • An autonomy policy per loop: stage, tags, rate and magnitude limits, named approvers
  • Citations on every recommendation to the recipe, spec or procedure it relied on
  • Model versions named in every record, with rollback by version
  • Export of the audit log and batch genealogy to your quality system

What the docs cover Developer overview

audit record · illustrative 
// one write, as the audit log would hold it
{
  "run": "run_scn_01",
  "step": "fill.seal",
  "agent": "agent.fill_seal",
  "stage": "bounded",
  "action": { "tool": "plc.write_setpoint", "tag": "FIL1.VALVE_14" },
  "limits": { "max_step": "declared per tag", "per": "declared per tag" },
  "evidence": ["vision.stream", "filler.read_telemetry"],
  "citation": "spec:CAN-330 fill-level v3 §2",
  "policy": "permitted",
  "models": { "fill_level": "versioned", "policy": "versioned" },
  "human": null,
  "outcome": "on target level · inside approved window"
}
Pricing

Priced per line, per plant, per group

Land on one workflow with a measured baseline. Expand by line, module, site and autonomy stage. Outcome components available on yield, loss, energy and water.

Line $14,000 per brewing, filling or packaging line / month

Brew, fill or pasteurization control, or inspection AI, for one line. For beverage makers validating ROI on the wedge.

  • One line, one agent module
  • Line-edge inference node
  • Connectors to the line's PLC and SCADA, analyzers and MES
  • Review console, alerting, audit log and genealogy
  • Shadow and assist stages, then bounded autonomy after the agreed gates
Start a pilot
Whole plant Plant $90,000 per plant / month

The whole plant: brew and blend, ferment and yeast, filter and carbonate, fill and seal, pasteurize and CIP, defect and inspect, quality and shelf life, yield and takt, robotic handling and the Cuvera twin.

  • All eleven agents and the orchestrator
  • Cuvera as-produced twin: the plan before the run
  • Defect-to-cause feedback across the plant
  • Water, energy, CO2 and CIP optimization
  • Whole-plant batch genealogy
Talk to us
Enterprise Custom land $650k – $8.5M ACV

Beverage groups standardizing on Brewira across sites, with custom recipe, product and tolerance models.

  • Multi-site plant-edge fleet
  • Custom recipe, product and tolerance models
  • SLAs and dedicated support
  • Outcome-based components on yield, loss, giveaway, water and energy
  • On-prem or private-cloud deployment
Contact us

Annual prepay

A 15 to 20% discount for annual prepayment.

Multi-year

Enterprise agreements with usage ramps.

Outcome components

A share of measured yield, loss, giveaway, water or energy improvement on the highest-value workflows.

Usage

Per-batch, per-line or per-action metering above plan limits.

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.

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

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

Enterprise

Standardize autonomy across the group

One policy model, one audit trail and one set of yield, loss, giveaway, water and energy benchmarks across every plant in the group, with each site's recipes and tolerance models kept private to that site.

Talk to us Enterprise details

  • Multi-site plant-edge fleet with shared model governance
  • Custom recipe, product and tolerance models per site
  • SSO and role-based access, named approvers (roadmap, 6 to 12 months)
  • Model versioning, validation reports and rollback
  • On-prem or private-cloud deployment
  • SLAs and outcome-based components on the highest-value workflows
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

Bring autonomy to one line

Start with one brewing, filling or packaging line and one measured baseline: giveaway, attenuation variance, CO2 per batch or energy per hectoliter. Shadow mode shows the number before anything is written.

Book a line review See pricing