Item classified
Coin recognition
AI
1881 Morgan Silver Dollar
Mint: Carson City
Deep mirror proof-like
Grade: MS67
Melt value: $43.64 USD
Counterfeit risk
the challenge
You know what's happening. Submission volumes are up. Way up. The same generational wealth transfer that's flooding marketplaces with collectibles is flooding your operation with items that need certified grades.
Your turnaround times are stretching from days to weeks. From weeks to months. Customers who used to wait are submitting to whoever can get them a grade faster. And you can't hire your way out of it - training a qualified grader takes years, not months.
Meanwhile, counterfeits are getting more sophisticated. The fakes that were easy to catch five years ago now require senior-level expertise to flag. Your best graders are spending time on items that shouldn't make it past the front door.
The math:
Submission volumes growing faster than you can hire and train
Senior graders spending time on routine items instead of edge cases
Turnaround times lengthening - competitors gaining submission share
New categories (trading cards, comics, luxury goods) creating demand your current team isn't staffed for
The problem isn't your people. Your graders are the best in the world. The problem is that there aren't enough hours in the day - and every new submission makes the backlog worse.
the solution
Vardera is AI infrastructure built to automate your grading workflows at scale.
Vardera’s AI models grade all of it at your items to your body's standard, so your reviewers stop spending their days on the obvious and start spending their days on the cases that actually need them.
Routine work, automated
Common items and standard condition calls clear before a reviewer sees them
Senior graders on the contested cases
Borderline calls, suspected fakes, edge cases, and high-value lots get full attention
Grades calibrated to your rubric
Not a generic scale, AI that grades to your scale
Consistency at volume
The 10,000th submission is graded like the first. No fatigue, no drift.
Your experts become the final stamp on decisions the AI has already made, applying their judgment where accuracy is genuinely contested, not where it's obvious.
how it works
Coins
Live
Trading Cards
Live
Toys & Action figures
Live
Beauty & Fragrance
in production
Luxury Handbags
in production
Sneakers & Streetwear
in production
more in production
The ROI Math
Current Operations
Current Operations
With Vardera
Automated grading with exceptions flagged for human review
Manual: every item reviewed by a human
Automated: counterfeits and misidentified items surfaced before review
Seconds to minutes
Consistency
Deploy a trained category model in weeks, calibrate on your historical data
Systematic - every item screened against the full counterfeit corpus
Your graders set the standard. Vardera applies it at the throughput your submission volume now demands. Your team's expertise lands where it's genuinely needed: the contested calls, not the routine ones.
grading bodies Use Cases
Clearing Submission Backlogs
Process more volume without lowering your bar
Peak submission seasons turn your pipeline into a bottleneck. Items sit in queue for weeks while customers wait - and some submit to competitors with faster turnaround.
Vardera's pre-screening layer processes your entire incoming queue and sorts it into tiers: high-confidence items your graders can verify quickly, edge cases that need deep expert review, and items that should be flagged or rejected. Your throughput increases. Your accuracy doesn't move.
Counterfeit Detection at Volume
Catch sophisticated fakes before they reach your graders
Counterfeits are getting better. The obvious fakes aren't the problem - it's the ones that require 15 minutes of expert scrutiny to identify. At volume, those 15-minute items add up to days of lost grader productivity.
Vardera's models are trained on known counterfeit patterns, casting anomalies, and authentication markers across hundreds of thousands of verified items. Suspected fakes get flagged automatically - with the specific anomalies highlighted - so your graders know exactly what to look for when they make the final call.
Expanding Into New Categories
Add trading cards, comics, or luxury goods without building expertise from scratch
Your customers are asking for grading in categories you don't currently cover. Building that expertise internally means years of hiring and training - and the submission volume is already there, waiting.
Vardera's deep category models give you production-grade analysis for new asset classes without starting from zero. Deploy a model, pair it with your grading team's quality oversight, and begin accepting submissions in new categories with confidence.
Preserving Consistency Across Your Team
Every grader starts from the same baseline
Grading consistency is what your certification depends on. But even your best graders have variance - driven by experience level, workload, fatigue, and subjective interpretation of borderline cases.
Vardera provides a consistent, data-driven baseline assessment for every item. Your graders don't start from a blank slate - they start from a structured analysis they can validate. The result: tighter grade distributions and fewer outlier assessments across your team.
FAQ's
Whether you're clearing a submission backlog, defending against sophisticated counterfeits, or expanding into new categories - Vardera gives your grading team the throughput they need without compromising the accuracy your certification demands.