Equipment OEMs
Brewhouse, fermentation, filtration and carbonation, filler and seamer, pasteurizer and CIP and inspection vendors shipping Brewira-ready autonomy on their machines.
Partners
Autonomy arrives through the people the plant already trusts.
Beverage plants buy from the equipment OEMs, MES vendors, analyzer suppliers and integrators they already work with. Brewira's distribution thesis is to ship through them: brewhouse, fermentation, filling, pasteurization and inspection vendors shipping Brewira-ready autonomy.
Illustrative scenario: Plant run · one lager batch from brewhouse to can · brewhouse, cellar, filler, tunnel pasteurizer. Not a measured run.
Program
Four kinds of partner
MES and automation vendors
Beverage MES, PLC and SCADA vendors whose systems carry the recipes, orders and genealogy Brewira reads and writes.
Analyzer and vision vendors
Inline gravity, CO2, dissolved-oxygen and turbidity analyzers and camera suppliers whose streams Brewira fuses at the line edge.
Beverage makers and co-packers
Design partners who run the first lines and shape the product; distribution compounds through the makers who prove it.
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.
Commercial
How the partnership would work
Stated as intent. No partner agreements are signed yet.
Brewira-ready equipment
Brewhouses, tanks, carbonation skids, fillers, pasteurizers and inspection stations shipped with the connectors, tags and limits Brewira needs, so a plant can start in shadow mode on day one.
Recipes in, genealogy out
Orders, specs and recipes read from the beverage MES; audit log and batch genealogy written back, with the MES remaining the system of record.
Streams fused at the edge
Gravity, CO2, dissolved-oxygen and turbidity analyzers and camera streams fused on the line-edge node into one process and inspection state.
Run timeline
What a partner-delivered run looks like
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
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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
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.
Fit
Who this works for
A good partner
- Sells into breweries and beverage makers in the $100M to $40B revenue range
- Owns a stage of the process or the data about it
- Has customers asking for yield, giveaway, water, energy or food-safety outcomes, not dashboards
- Will co-develop connectors with a design partner
Not yet
- Resellers looking for a finished product to list this quarter
- Integrators expecting a certification program; none exists yet
- Anyone who needs customer references before the first pilot has run
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.
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
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.
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.
- 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.
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
Bring autonomy to your customers' plants
If you sell to breweries and beverage makers, the first conversation is about one of their lines.