Every model, prompt and policy that can touch a line carries a version, and the run record names the versions that produced it.
Changelog
Every release that can touch a line, written down.
Nothing has shipped to a plant yet. This is the release line the first design partners will see, in the order it is planned, plus the policy that governs how any release reaches a line.
Illustrative scenario: Plant run · one lager batch from brewhouse to can · brewhouse, cellar, filler, tunnel pasteurizer. Not a measured run.
Releases
The planned release line
Status is honest: everything is queued. Order follows the first-release plan.
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v0.1Connectors and shadow mode QUEUED
Connectors to the wedge line's PLC and SCADA, inline analyzers, filler and inspection systems, lab system and beverage MES. Read-only. Predictions logged against lab, QA and PLC outcomes; nothing written.
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v0.2Review console and audit log QUEUED
The console where brewmasters, process engineers and quality managers approve, correct and annotate; the immutable, assurance-grade food-safety audit log from day one.
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v0.3Assist mode QUEUED
Recommendations for brew, fermentation, carbonation, fill and seal or pasteurization and CIP moves with the evidence and citation behind each one; approvals and corrections become labeled training events.
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v0.4Bounded autonomy QUEUED
Guarded writes to low-risk filling, carbonation and inspection loops inside documented recipe, quality, food-safety, equipment and rollback limits, after the food-safety and ROI gates.
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v0.5Cuvera: the plan before the run QUEUED
One standard product family simulated on one line and calibrated against as-produced batches; pre-run plan suggestions to one execution agent; a validated synthetic rare-defect set.
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v0.6Second module in the plant QUEUED
An adjacent agent on the same plant with deeper integrations; SSO and role-based access; SOC 2 Type II in progress.
Policy
How a release reaches a line
Golden datasets and model-as-judge evaluations gate model and prompt changes in CI.
Nothing reaches a plant until its predictions have been compared to that plant's lab, QA and PLC outcomes in shadow mode.
Rollback by model version; a Brewira outage returns the plant to its existing control.
Run timeline
The reference scenario each release is tested against
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
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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
What the tool log will show per release
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.
- 04:50:02mes.read_order({ batch: "L-0931", brand: "LAGER-33", package: "CAN-330" })
- 04:50:02ok recipe locked · HACCP plan v6 · CCP: tunnel PU 15–20
- 04:50:03lab.read_results({ yeast_lot: "Y-2207", test: "viability" })
- 04:50:03ok viability inside window · lot accepted for pitching
- 04:50:04twin.simulate({ candidates: 24, horizon: "batch" })
- 04:50:42ok best plan #7 · PU margin held · lowest CO2 and energy per hl
- 04:50:43policy.evaluate({ plan: 7, stage: "bounded" })
- 04:50:43ok 7 writes permitted · 1 write requires human approval
- 04:50:44plc.write_setpoint({ tag: "BH1.BLEND_RATIO", basis: "gravity+recipe" })
- 04:53:24ok wort gravity on recipe · utilization held
- 05:10:00ferment.predict_curve({ tank: "FV-12", lot: "Y-2207" })
- 05:10:00ok attenuation curve predicted · finish day 5 · crash timed
- 05:10:01plc.write_setpoint({ tag: "FV12.TEMP_RAMP", window: "brewmaster_approved" })
- 05:10:01ok ramp applied · no stuck or runaway ferment flagged
- 06:02:10plc.write_setpoint({ tag: "CARB1.CO2_DOSE", basis: "co2+do+turbidity" })
- 06:05:25ok CO2 on package target · clarity inside spec · backwash timed
- 06:05:26vision.stream({ cameras: 16, models: ["fill_level", "seam_cap", "label_ocr", "foreign_body"] })
- 06:31:48reject: low fill · can 20417 · attributed to filler valve 14 drift
- 06:31:49defect.attribute({ event: "low_fill", cause: "filler.valve_14" })
- 06:31:49ok fill_seal notified · valve 14 trimmed inside window · two more rejects, then clean
- 06:31:50plc.verify_pu({ tag: "TUN1.ZONES", profile: "validated" })
- 06:31:50ok PU inside profile · readings → audit log
- 06:31:52approval.request({ action: "cip.window", reason: "overlaps next brand start" })
- 06:33:44ok approved by the shift quality manager · PU profile untouched · tighter release check
- 09:12:30mes.release_batch({ batch: "L-0931", genealogy: "full" })
- 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.
Roadmap
What comes after the first release
From the roadmap, by horizon.
| Horizon | Planned |
|---|---|
| 0–6 months | Three to five design partners on the wedge workflow; MVP: connectors, agent loop, review console, assurance-grade food-safety audit log; accuracy and loss, giveaway and water-and-energy ROI proven in shadow then assist; SOC 2 Type I in progress; IP-safe deployment |
| 6–12 months | Design partners convert to paid; graduated autonomy on low-risk filling, carbonation and inspection loops; Cuvera hit-quality-before-run; second module per plant; SOC 2 Type II; SSO and RBAC; first enterprise logos; food-safety and sustainability assurance packages |
| 1–3 years | The full brew, ferment, carbonate, fill, pasteurize and inspect loop; single plant to multi-site maker to global group; equipment-OEM and MES-vendor channels; international expansion; benchmark data products |
| 3–10 years | The autonomous system of action for brewing and beverage manufacturing, with adjacent scopes through packaging and cold chain and a platform and API ecosystem |
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.
| Stage | What the agent does | What the person does | When |
|---|---|---|---|
| Shadow | Predicts gravity, attenuation, carbonation, fill and seal faults, contamination and takt; writes nothing | Runs the plant as today; compares predictions to lab, QA and PLC outcomes | First phase with every design partner |
| Assist | Recommends bounded brew, fermentation, carbonation, fill and seal, pasteurization and CIP moves with the evidence | A brewmaster, process engineer or quality manager approves or rejects each one | After accuracy is proven against the baseline |
| Bounded | Writes low-risk filling, carbonation and inspection setpoints inside documented recipe, quality, food-safety, equipment and rollback limits | Approves anything above the limits; reviews the shift record | After the food-safety and ROI gates agreed up front |
| Exceptions | Escalates anything outside its envelope, CCP-adjacent moves and release decisions | Always decides these; the agent never does | Permanent |
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.
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.
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.
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.
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.
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.
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.
Data engineering
Image, time-series and batch-genealogy ETL for feature generation, quality correlation and cross-plant benchmarks on the GPU.
Robotic handling
Pack, case and palletizing handling, with perception and motion policies built and validated in simulation before they move a pallet.
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
| Item | Scope | Status |
|---|---|---|
| SOC 2 Type I | Cloud control plane | QUEUED Roadmap, first 6 months |
| SOC 2 Type II | Cloud control plane | QUEUED Roadmap, 6 to 12 months |
| HACCP · FSMA · FSSC 22000 · BRCGS | Grounding and record-keeping | RUNNING Design basis for retrieval and the audit log |
| Per-tenant isolation | Data, memory, models | RUNNING Design rule |
| On-prem deployment | Recipe-sensitive producers | RUNNING Design option |
Brewira supports your food-safety records. It is not a certification and it does not replace your HACCP plan.
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.
PLC and SCADA of brewhouse, blending and syrup systems, fermentation tanks and yeast handling
Setpoint reads, guarded writes, interlocks untouched
Filtration and carbonation skids and their inline CO2, dissolved-oxygen and turbidity analyzers
Continuous carbonation and clarity state
High-speed filler, seamer and capper controls
Telemetry in; fill-valve and seam settings inside approved windows
Tunnel and flash pasteurizers, CIP skids and hygiene sensors
PU readings verified and logged; CIP release checks
Multi-camera stations for fill level, seal and cap, label, foreign body and container defects
Frames, defect events, reject commands
Orders, recipes, product specs, batch genealogy, LIMS results
Targets in, release records out
Plant and asset meters; Isaac-driven pack, case and palletizing cells
Hard constraints for scheduling; bounded handling
SSO and role-based access; SOC 2 on the roadmap
Named approvers, scoped roles
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.
Critical control points are not optimization variables. The pasteurization PU profile, the CIP release checks and the batch release decision stay with your HACCP plan and your people. Brewira verifies readings, writes them to an immutable audit log and attaches them to the batch genealogy. It is grounded in HACCP, FSMA, FSSC 22000 and BRCGS procedures; it is not a certification and does not replace your plan.
Brewira sits above your existing automation as a supervisory layer. If it stops, the plant keeps running on its current PLC and SCADA control and the interlocks it already has. A Brewira outage degrades the plant to the way it runs today, not to a stop.
The first phase is shadow mode on one line: Brewira reads your analyzers, PLC history, lab results and MES while you run the plant as usual, and we measure its predictions against your lab, QA and PLC outcomes. Recommendations start when accuracy is proven against that baseline, and improve as plant-specific history and brewmaster corrections accumulate.
Recipes, product specs, tolerance models and supplier data are tenant-scoped and never used to train another customer's models. Retrieval is multi-tenant isolated and permission-aware. Cross-plant learning, where a customer opts in, is federated and IP-isolated. On-prem deployment is available for producers protecting sensitive recipes.
You are, the same as with any control strategy. That is why every write is policy-checked, bounded, logged and reversible, every output carries a citation to the recipe or procedure it relied on, and anything above your threshold waits for a named approver. The audit log records the request, the reasoning, the limits applied and the human decision.
As a design partner, on one line, with one hard metric: fill giveaway and low-fill rejects, leaker and seal faults, attenuation variance and tank time, CO2 use and clarity rejects, or water and energy on pasteurization and CIP. We instrument the line in shadow mode, measure the baseline, move to assist mode when accuracy is proven, and expand only when the number holds.
Full multi-module autonomy across the whole plant, long-tail integrations beyond the design partners' stacks, and self-serve onboarding. The first release is one wedge workflow, its connectors, the agent loop with human checkpoints, the review console and the assurance-grade food-safety audit log.
Get started
Follow the release line
Design partners see each release before it reaches their line. Ask to be one.