Food & Beverage · Production quality vision
Your line runs at 400 units a minute. Your quality check runs at human speed.
Banao deploys computer-vision inspection on food and beverage production lines — checking fill levels, seal integrity, label placement, date-code legibility, and foreign-matter signals frame by frame, at line speed, without slowing throughput.
The model runs on your existing line cameras where imaging allows, integrates with your PLC and reject hardware, and produces a real-time defect feed your quality team can act on — not a report compiled after the batch has shipped.
The first call is free · 45 minutes · no obligation
What we build
What a Banao production quality vision deployment covers
Each check targets a defect class with a measurable cost: a seal failure that reaches a retailer, a fill under-spec that fails a net-content audit, a label misprint that triggers a recall. We start where the cost is quantifiable.
Fill-level detection across bottle, can, and pouch formats
Vision models that read fill level against your specification at line speed — catching underfill and overfill before they leave the filler station and reach the packer. Configured per SKU, per container format.
Seal integrity and closure checks
Induction seals, heat seals, foil lids, and cap presence inspected on every unit — flagging the partial seal and the missing cap before a compromised product reaches distribution. Output drives your reject gate directly.
Label placement, print quality, and date-code legibility
Label position, wrinkle, and print-quality checks, plus date-code and batch-code legibility verified by OCR — so a blurred best-before date is caught at the line, not by a retailer's incoming quality team.
Foreign matter and contamination signals
Vision-based foreign-matter screening as a secondary check layer, covering visible contaminants in transparent containers and surface anomalies that indicate product contamination. Works alongside your existing x-ray or metal-detection equipment, not as a replacement.
Colour, appearance, and product-specific defect checks
Colour deviation, surface defects, and product-specific appearance checks — blemishes, clumping, coating coverage — trained on your grading standards. Relevant for baked goods, confectionery, fresh produce, and coated snacks where appearance is part of the specification.
PLC integration and food-grade environment specification
The model output drives your existing reject equipment — pneumatic ejectors, diverter gates — and camera mounts are specified for your washdown, humidity, and temperature requirements. We do not fit a generic industrial enclosure in a 4°C wet zone.
Receipts
Where this is already running
Metrics shown dotted (··) are being finalised in our case-study metrics pack — published only once verified. Client details anonymised at client request.
Seal and fill inspection deployed across multiple SKU formats
Seal failures were reaching the retailer at low but consistent rates — invisible at the line and only surfaced through complaints. Banao trained a seal-inspection model on historical reject imagery, deployed it edge-side on existing line cameras, and wired the output to the reject gate. Manual end-of-line sampling dropped for seal checks; catch rate at the line increased.
Dogfooding
We run our own AI before deploying it on your line
Banao operates a ~300-person engineering company on its own AI products. InterviewGod screens our own engineering hires every week. Vikaas runs our own demand-generation pipeline. We do not ship a system to a production environment that we have not already depended on ourselves.
A food-line inspection model carries the same standard: it has to perform on real production data, at real line speeds, with real defect variation — not on a controlled test set assembled for a proposal. That is the bar we set before a client's quality team sees the first result.
Screens Banao's own engineering hires every week.
Runs Banao's own demand-gen pipeline end to end.
The honest version
When production quality vision is the wrong investment
Vision inspection is not the right answer for every line. We will tell you before you spend on one:
- Imaging environment not viable: washdown-heavy, heavily steam-obscured, or low-light zones can make consistent imaging impractical without significant lighting and enclosure engineering. The Discovery Sprint establishes what the imaging challenge actually costs before any model work starts.
- Low volume or high SKU variability: for short-run or highly variable SKU sets where the line changes format every hour, a vision model needs frequent reconfiguration. Below a minimum run length, a trained line inspector remains cheaper — we will tell you where that threshold sits for your operation.
- Already covered by specialist equipment: if your line already runs x-ray detection for your primary hazard category, adding a vision layer for the same defect class may not add detection value. We map what your current equipment covers before scoping any additional build.
How we start
How we start — prove it on your line before you build it
We do not quote a vision deployment off a camera spec sheet. We look at your actual line, your defect history, and your imaging conditions first.
- 01
AI Discovery Sprint
2 weeks · fixed price
We audit a sample of your line camera footage or arrange a controlled imaging session on your product, test feasibility on your hardest defect classes, and hand back a baseline detection accuracy estimate and ROI maths — yours to keep regardless of next steps. If you proceed, the Sprint fee is credited against the build.
- 02
Build
Label, train to your grading rules and SKU formats, and integrate with your cameras, PLCs, and reject hardware. Food-grade camera mounts, lighting design, and data pipeline are part of the deliverable — not assumptions carried forward from the spec.
- 03
Production & continuous improvement
Edge deployment with operator override, a production dashboard showing defect rates by line and shift, and a feedback loop so quality-team corrections sharpen the model across SKU transitions.
FAQ
Frequently asked questions
Can the model handle our line speed? We run at 400+ units per minute.
Throughput is a camera and hardware question as much as a model question. The Discovery Sprint includes a camera and frame-rate audit for your specific line speed and container format. Inference at 400+ units per minute is achievable with the right edge hardware — we establish the exact configuration in week one before any model development starts.
We have 30+ SKUs and frequent format changes. How does the model handle that?
Each SKU gets its own configuration — fill specification, label template, seal type — so the model switches profile when the line changes format. For very high SKU counts with short runs, the Discovery Sprint will establish whether the reconfiguration overhead is manageable or whether a rules-based check is more practical for certain format classes.
Our cameras are already running for CCTV. Can you use those?
Possibly. It depends on camera placement, resolution, and whether the imaging angle and lighting give the model enough signal for your target defect class. The Discovery Sprint audits what your existing cameras can see and identifies where additional lenses or lighting are genuinely needed — not as a default assumption.
Does this work alongside our existing x-ray or metal-detection equipment?
Yes. Vision inspection addresses defect classes that x-ray and metal detection do not cover well — fill level, label accuracy, seal appearance, date-code legibility, colour and surface defects. We scope the vision layer to complement your existing equipment rather than duplicate it. The Discovery Sprint maps the coverage gaps your current process leaves.
What happens when the model makes an incorrect call?
Operator overrides are built into the standard deployment. Incorrect calls are logged, reviewed, and fed back into the model's next update cycle. Your quality team sets the sensitivity threshold and retains full authority over any product disposition decision — the model surfaces calls, it does not make final quality judgements without a human override path.
Get started
Bring your hardest defect class to a 45-min call
Show us the defect your current process misses most — a seal failure, a fill variance, a date-code error at line speed. In 45 minutes we will tell you whether vision inspection is worth building for your line and what it would take.
Book a Discovery Sprint