About Rexolution

We are changing how PCB-A gets
visually inspected — at the root.

Rexolution — a vision AI company founded by SNU and KAIST alumni.

1 /

PCB assembly OQC still depends on an operator’s eyes and is done by hand. Inspection quality therefore tracks whoever happens to be on shift. To fix that, a group of SNU and KAIST alumni founded Rexolution.

2 /

Our AI vision inspection system automates OQC and lifts throughput where it actually matters. Conventional AOI needs teaching and debugging for every new product; REX inspects immediately, with no teaching, which makes it a solution built for high-mix, low-volume production.

3 /

From the hardware to the model, everything is built in-house — which is where the reliability comes from. A dedicated support hotline means service and on-site issues get answered fast.

Rexolution co-founders — Hyuk Kim (CEO), Chulmin Lee (CTO), Sungsik Kang (COO)Rexolution co-founders — Hyuk Kim (CEO), Chulmin Lee (CTO), Sungsik Kang (COO)
Incorporated
'24.08
Rexolution Inc. founded
Deployment Sites
10+ sites
In Korea and abroad, two years from incorporation
Global Validation
USA
Field validation completed at East/West, Texas, USA (Jun 2026)

Deployments

Deployments — Korea & Overseas

Two years from incorporation, more than ten sites are running Rexolution equipment. They range from high-mix shops inspecting ten or more board types a day to volume producers pushing over two thousand boards. Real productivity and reliability, proven across very different manufacturing environments — and the footprint keeps growing.

Geumcheon, Seoul · REX 1.5
Geumcheon, SeoulREX 1.5
Hwaseong, Gyeonggi · REX 1
Hwaseong, GyeonggiREX 1
Ansan, Gyeonggi · REX 1
Ansan, GyeonggiREX 1
Suwon, Gyeonggi · REX 1
Suwon, GyeonggiREX 1
Hwaseong, Gyeonggi · REX 1.5
Hwaseong, GyeonggiREX 1.5
Geumcheon, Seoul · REX 1.5
Geumcheon, SeoulREX 1.5
Geumcheon, Seoul · REX 1.5
Geumcheon, SeoulREX 1.5
Seongnam, Gyeonggi · REX 1
Seongnam, GyeonggiREX 1
Overseas — Austin, Texas, USA

REX 1.5, validated in Texas

We installed a REX 1.5 at East/West in Austin, Texas and completed a month of field validation there in June 2026. What they valued most was being able to inspect immediately on a product change, with no teaching — and that THT components are covered too. It has been running without issue since.

REX 1.5 shipped to East/West
The Rexolution and East/West teams
East/West headquarters, Austin, Texas
REX VISION AI

Compare placement.
Find fine cracks.

01 / THT

Read placement differences against a reference.

Polarity recognition with PCB-A-specific AI

REX uses PCB-A-specific AI to distinguish polarity marks and orientation cues. Comparing each component with a normal reference verifies its placement direction and detects reversed insertion.

Robust defect detection across component tilt and camera viewing angles

REX consistently detects defects by comparing the same component’s core features, even when its tilt or the camera viewing angle changes.

Inspection examples

The same component, a different orientation

Prediction · Reversed
Model feature visualization
01Reference image
Reversed · capacitor · Reference image
02Inspection image
Reversed · capacitor · Inspection image
03Reference differences
Reversed · capacitor · Reference differences
04Inspection differences
Reversed · capacitor · Inspection differences

The polarity band appears on the opposite side of the capacitor. Check the orientation in the inputs, then inspect feature differences and attention separately.

Dark → bright · local feature difference

Bright regions have fewer similar local features in the other image. Colour is not defect probability; imaging and surface variations can also cause a response.

How reference-based inspection works
  1. 01 / Reference comparison

    Extract comparable features

    The reference and inspected component pass through the same network.

  2. 02 / Spatial features

    Distribute attention, retain position

    Features from different component regions are compared together with their positions.

  3. 03 / Pair verification

    Classify the relationship

    Feature differences and similarities distinguish aligned, reversed, and wrong or missing parts.

A change in orientation is not always a defect. Component polarity and the applicable inspection criteria also matter.

THT VALIDATION

Performance, with evaluation context

Internal validation · 9,568 pairs Includes unseen boards

Macro-F1
0.970

Equal-weight mean F1 across three classes

Normal false-positive rate
0.65%

6,183 cross-board normal pairs

F1 by class0–1 · higher is better
ClassF1Pairs
Aligned
0.993
7,796
Reversed
0.930
624
Wrong / missing
0.987
1,148

F1 is the harmonic mean of precision and recall. These are internal THT validation results, not measurements of the SMD crack model or a guarantee across production conditions.

02 / SMD CRACK

Reveal fine surface cracks as anomaly signals.

Inspect cracks and damage on SMD component surfaces. The inspection image sits beside its anomaly heatmap so you can compare the physical damage with the model response.

01Fine crack
Fine crack · InspectionInspection
Fine crack · Anomaly heatmapAnomaly heatmap
02Open fracture
Open fracture · InspectionInspection
Open fracture · Anomaly heatmapAnomaly heatmap
03Surface damage
Surface damage · InspectionInspection
Surface damage · Anomaly heatmapAnomaly heatmap
Red overlay · anomaly response

Qualitative research examples. Colour intensity is not a shared probability scale across images and does not specify an exact crack boundary or detection rate.

Synthetic data for rare defectsData augmentation example

This study synthesizes defects on normal images and compares their appearance with real damage. The middle image is synthetic, separate from inspection results and evidence of detection performance.

Normal input
Normal input
Synthetic defect
Synthetic defect
Real defect reference
Real defect reference

Team

Team — 6 Members
Hyuk Kim
CEO

Hyuk Kim

M.S. Management of Technology, KAISTFormer Director & Head of Strategy, Twinny (autonomous mobile robots)
LinkedIn ↗
Chulmin Lee
CTO

Chulmin Lee

B.S. Mechanical Engineering, Seoul National UniversityRoboCup 2023, Bordeaux — championPresidential Science Scholar, 2018
LinkedIn ↗
Sungsik Kang
COO

Sungsik Kang

B.B.A., Seoul National UniversityCertified Public Accountant (KICPA)Former Senior Associate, PwC Samil
LinkedIn ↗
Researcher

Hyojun Shin

Backend Engineer

Sanggyun Bang

LinkedIn ↗
AI Engineer

Ansh Gopinath

LinkedIn ↗

History & awards

History & Awards
  1. Investment from Hustle Fund, a Silicon Valley venture capital firm
  2. Selected for the NVIDIA Inception Program, 2025
  3. G-Valley Startup Competition 2025Grand Prize
  4. Selected as a joint-research startup with Mila (Quebec AI Institute), Canada
  5. Bucheon Startup League 2025Grand Prize
  6. Seocho Startup Station IR Competition 2025Grand Prize
  7. Selected for Google for Startups Accelerator 2025 (APAC / Deep Tech)
  8. China / UK Global Startup Competition 2025Excellence Award
  9. Selected for KDB NextONE Seoul, Cohort 10 (2025)
  10. Selected for TIPS R&D
  11. Vietnam TECHFEST IR Competition 2024Excellence Award
  12. Top 10, Golden Panda Global Startup Competition 2024 (China) ↗
  13. Rexolution Inc. certified as a Venture Company
  14. Daedeok Innopolis Deep Tech Startup Competition 2024Excellence Award
  15. Pre-seed round raised (Antler Korea) ↗
  16. Rexolution Inc. incorporated
  17. Selected for Seed TIPS

Partners

Partners & Programs
Hustle FundAntlerNVIDIA Inception ProgramGoogle for Startups AcceleratorMila — Quebec AI InstituteKDB 산업은행TIPS KOREA