Pricing

Plans That Scale with Your Lines

From single-line PoCs to global deployments, LIVIS pricing grows with your operation and your ROI.

Pilot

Validate AI inspection on one line

Features
Plant

Scale across lines within one site

Features
Enterprise

Standardize AI inspections company-wide

Features

Included With Every Plan

Custom-Fit Solution

Every factory runs differently, and one-size-fits-all tools rarely work. We diagnose your setup on-site and deliver a solution tailored to your needs.

Smooth Onboarding

New technology is exciting but can feel overwhelming. With guided setup and hands-on training, your team gets inspection-ready from day one.

Same-Day Response

Issues shouldn’t stop your line. Get fast answers through email, Slack, or direct support whenever problems arise.

Always Up to Date

Benefit from regular updates that keep your inspection system smarter and always current.

Comparison

From Hidden Costs to Measurable Gains

What manufacturers lose with traditional inspection 
and what they gain with LIVIS.

Without LIVIS

Missed Defects
Recalls & brand damage ($500K–$50M+)

False Rejects
Good parts scrapped ($100K–$500K/year)

Downtime
Lost revenue + missed SLAs ($10K–$100K/day)

Manual Tuning
Engineering hours lost ($50K–$200K/year)

Blind Spots
No traceability or RCA

Training Complexity
Long onboarding cycles

With LIVIS

Missed Defects
Recalls & brand damage ($500K–$50M+)

False Rejects
Good parts scrapped ($100K–$500K/year)

Downtime
Lost revenue + missed SLAs ($10K–$100K/day)

Manual Tuning
Engineering hours lost ($50K–$200K/year)

Blind Spots
No traceability or RCA

Training Complexity
Long onboarding cycles

Frequently asked questions

How many images or samples are needed for training the AI model?

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

Unlike most AI-based systems, LIVIS requires minimal data for training. Typically 30 samples per defect and 30 good samples are sufficient to develop the model.

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