Trust before autonomy
Grounding, audit, human-in-the-loop and graduated control come before any write to a line.
About
Beverages move at tens of thousands an hour. The plant should not run on memory.
Brewira exists to move the craft of brewing and beverage manufacturing into reliable, auditable AI, so every batch is safer, higher-yield and less wasteful. The plant runs itself; the people who know the product decide how far.
Illustrative scenario: Plant run · one lager batch from brewhouse to can · brewhouse, cellar, filler, tunnel pasteurizer. Not a measured run.
Why
Why we are building this
Beverages are among the highest-volume packaged products on earth: beer, soft drinks, water, juice, energy and functional drinks, RTD and dairy-alt, brewed, blended, carbonated and filled on some of the fastest lines in all of manufacturing. Running a beverage plant is still one of the most craft-bound, water- and energy-intensive and loss-heavy processes in food and beverage.
Wort and blends are brewed to exact gravity and flavor, fermented to exact attenuation, filtered and carbonated to exact clarity and CO2, filled at enormous speed to exact level and sealed without leakers, pasteurized for stability, and inspected for fill, seal, label, foreign bodies and container defects. A drift at any step is loss, giveaway, downgrade, spoilage, a recall or a food-safety event.
Most plants run this on fixed recipes and line setpoints, spot lab tests and the judgment of a shrinking pool of brewers and operators. The tools they have measure and log. None of them act. That is the gap.
Why now
- The functional, low- and no-alcohol, RTD and energy-drink boom
- Premiumization and SKU proliferation
- Sustainability and water and energy mandates on brewing, CIP and pasteurization
- Food-safety and traceability pressure and recall cost
- A brewer and line-operator shortage on lines that never stop
- Machine vision, inline analyzers, edge AI, robotic packaging, pasteurization and CIP automation and process twins finally mature for high-speed beverage lines
Principles
How we build
Every correction trains the system
A brewmaster's or quality manager's correction is a labeled training event, not a complaint.
Land narrow, expand relentlessly
One line and one number first. The plant and the group follow the number.
Food safety is not a variable
Pasteurization units, CIP release and batch release stay with the plant's HACCP plan and its people.
Tenant isolation is a design rule
Recipes and supplier data never cross a customer boundary. On-prem is an option, not an exception.
Evaluation gates every change
Golden datasets and model-as-judge evaluations gate model and prompt changes in CI.
Run timeline
What we are actually building
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.
Focus
What kind of company this is
What we are
- An independent startup building original physical-AI software for brewing and beverage manufacturing
- A product company: recurring software, priced per line, per plant and per group
- GPU-essential by design: line-edge vision, analyzer fusion, process and CFD twins, synthetic rare defects, model training
- Brewing and beverage only, from brewhouse to pallet
What we are not
- Not a consultancy, systems integrator or outsourced development firm
- Not a reseller or a division of an equipment OEM
- Not a dashboard; a system that acts, with a person above the threshold
- Not claiming customers, results or certifications we do not have
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.
Market
The market
Beverage manufacturing automation, brewhouse and fermentation control, filtration and carbonation, high-speed filling and seaming, pasteurization and CIP, packaging inspection, beverage MES and factory software. Autonomous brewing and filling control, contamination and fill and seal sensing and beverage digital twins are the fastest-growing segments.
$17B
Total addressable market: beverage manufacturing automation, brewhouse and fermentation control, filtration and carbonation, high-speed filling and seaming, pasteurization and CIP, packaging inspection, beverage MES and factory software
$4.2B
Serviceable market: the segments Brewira can serve with its product and go-to-market
$260M
Obtainable within three years through land-and-expand across brewing, filling and packaging lines
~11%
Annual growth of the addressable spend
Team
Who is building it
Brewira is led by its founder and CEO, James Harrington, and its CTO, Adam Mercer. The profiles below describe what each of them owns and the ground they cover.
Founder & CEO
James Harrington
James runs the company and owns the design-partner relationships, the pilot structure and the commercial model. He decides which brewery or beverage plant and which line go first, what loss, yield, water or energy number a pilot is judged on, and who in the plant signs off on the baseline.
Focus: brewing and beverage production operations, plant economics, partnerships and go-to-market.
CTO
Adam Mercer
Adam owns the plant-edge runtime, the fermentation, carbonation, filling and inspection models, the batch digital twin, and the audit architecture behind every Brewira agent. He is accountable for the bounded, logged write-back into brewhouse, fermenter, filler and pasteuriser controls, and for every agent starting in shadow mode.
Focus: edge computer vision, process control, simulation and digital twins, safety-critical industrial software.
Hiring
The roles we are building around are on the careers page. We look for people with hands-on brewing or beverage production, applied AI at the edge, and experience shipping regulated, safety-critical software or hardware.
The name and the mark
Brewira is built on brew, the defining act of beverage production, with an ending that matches the portfolio it belongs to. The mark is a fermenting vessel with rising bubbles: a tall rounded capsule that reads as both a fermentation tank and a can, a wavy liquid line separating the headspace from the liquid, and three bubbles of growing size rising in a loose diagonal for fermentation and carbonation. It covers the brewhouse-to-can path in one object.
Green for hops and for the water and energy recovery work; the headspace in deep green on light backgrounds and pale green on dark ones.
Writing
Recent notes
Giveaway, poured out by the container
A beverage line fills tens of thousands of containers an hour, and still over-fills every one of them to avoid a low fill. That giveaway is pure margin, poured …
The craft is walking out the door
The best brewers and line operators hold the recipe in their heads. Gravity gets checked by spot sample, attenuation by experience, fill level by over-filling t…
Why a twin has to be as-produced, not as-designed
Plants commit to a recipe, a yeast lot, a package and a schedule, and only discover a gravity miss, a slow ferment, a carbonation drift or a takt bottleneck aft…
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.
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.
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.
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.
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.
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
Come build the plant's operating system
Design partners, future colleagues and the people who sell to beverage plants: the first conversation is about one line.