No guessing. No gray areas. Clear, honest answers about AI grading, card condition, submissions, and how AGS compares.
AGS is the only card grading company that uses fully automated AI and machine scanning to grade cards with measurable accuracy and zero human subjectivity.
Your card is scanned, analyzed by AI models, defects are measured, a grade is calculated, and you receive a slab + digital report + Heightmaps.
Yes. AGS is the only grading company that uses a complete AI + robotic grading pipeline.
Those companies use human graders. AGS uses machine vision + AI for consistency, accuracy, and transparency.
No. The grading pipeline is fully automated.
AI produces measurable, repeatable results with zero fatigue, bias, or opinion.
Yes — the same algorithms produce the same result on the same card, every time.
Yes. Cards are scanned and analyzed entirely by machines.
AGS launched in 2021 and is the first true AI grading company.
Pokémon, sports cards, trading cards, modern, vintage, holo, chrome, textured, and more.
Yes — Pokémon is one of the most graded categories.
Yes — basketball, football, baseball, soccer, F1, etc.
Yes, both are supported.
Yes — centering, corners, edges, and surface.
Yes — every card gets a full digital scan report.
A visual map showing where the AI detected defects.
Red = severe flaws, orange/yellow = moderate flaws, green = clean areas.
Yes — all graded cards appear in real-time pop reports.
On the slab's label and inside your digital report.
Yes — bulk pricing and group submissions are supported.
AGS is headquartered in the United States with satellite grading labs.
Yes — AI grading removes bias and provides transparent data.
High-clarity polymethyl methacrylate (PMMA) engineered for optical transparency.
Yes — slabs use tamper-evident ultrasonic seals.
By storing a digital fingerprint + scan report for every card.
AI analyzes images, detects defects, measures centering, and calculates a grade based on data.
Deep learning models for detection, segmentation, texture analysis, and geometric measurement.
By analyzing pixel patterns, light reflections, textures, and depth variations.
Yes — AI detects unnatural edge geometry and fiber inconsistencies.
Yes — discoloration patterns and ink-layer mismatches are identified.
Yes — fake cards show detectable inconsistencies in color, texture, and print structure.
Yes — including incorrect font, texture, gloss, and border patterns.
By detecting borders and calculating exact pixel ratios.
Through corner-shape analysis and micron-level deviation detection.
Using segmentation, reflectivity changes, and edge-profile scanning.
Through light reflection mapping, texture analysis, and depth scanning.
Yes — microscopic scratches are easily detected.
Yes — via depth analysis and texture distortion detection.