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Easy Customizable Optimized Solution

AI Visual Inspection System - Fully customizable & integrated with robotics by design.
Industrial AI solutions with only design drawings or small dataset

1

We utilize highly skilled engineers in Vietnam at affordable prices.

2

We utilize highly skilled engineers in Vietnam at affordable prices.

3

We utilize highly skilled engineers in Vietnam at affordable prices.

Balancing quality and price

Balancing quality and price

Balancing quality and price

Balancing quality and price

標準価格

200万円~

検査ソフトウェアと以下のハードウェア

含みます

1.カメラ:2000万画素の Image Source 製もしくはBalser 製

2.GPU付きPC

3.PLC連携とのDIO

Resolving issues regarding system construction procedures and time

1 to 4 weeks

1 to 4 weeks

2 weeks or more

PoC implementation verification

  • Free verification possible on existing devices (iPad, PC)

  • Using unsupervised learning technology , verification is possible with little data

System development, implementation, operation and maintenance

  • Offering plans (Express, Pro) to suit your needs

  • Use of standard UI reduces implementation time

PoC implementation verification

導入事例

不良品検査

(傷、打痕などの検査)

System overview

  A system that predicts sales of the entire store and each product by utilizing POS data of the retail business, weather information acquired from the outside, and trend information. It can also be used for past sales analysis and trend analysis.

 

Client

  Stationery sales

 

Effect after system introduction

   We were able to place orders at the right time, reduce defective inventory and missed sales, and improve profits by about 5%.

 

Technology

• Prediction engine: RNN model, LightGBM model

• Framework: Keras, Flask

• Language: Python

Development scale

  2 people x 4 months

図14.jpg

ネジのカウント

System overview

  A system that predicts sales of the entire store and each product by utilizing POS data of the retail business, weather information acquired from the outside, and trend information. It can also be used for past sales analysis and trend analysis.

 

Client

  Stationery sales

 

Effect after system introduction

   We were able to place orders at the right time, reduce defective inventory and missed sales, and improve profits by about 5%.

 

Technology

• Prediction engine: RNN model, LightGBM model

• Framework: Keras, Flask

• Language: Python

Development scale

  2 people x 4 months

図1.jpg
IMG_3463.JPG

不良品検査 (染み検査)

System overview

  A system that predicts sales of the entire store and each product by utilizing POS data of the retail business, weather information acquired from the outside, and trend information. It can also be used for past sales analysis and trend analysis.

 

Client

  Stationery sales

 

Effect after system introduction

   We were able to place orders at the right time, reduce defective inventory and missed sales, and improve profits by about 5%.

 

Technology

• Prediction engine: RNN model, LightGBM model

• Framework: Keras, Flask

• Language: Python

Development scale

  2 people x 4 months

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寸法検査(1cmの部品)

System overview

  A system that predicts sales of the entire store and each product by utilizing POS data of the retail business, weather information acquired from the outside, and trend information. It can also be used for past sales analysis and trend analysis.

 

Client

  Stationery sales

 

Effect after system introduction

   We were able to place orders at the right time, reduce defective inventory and missed sales, and improve profits by about 5%.

 

Technology

• Prediction engine: RNN model, LightGBM model

• Framework: Keras, Flask

• Language: Python

Development scale

  2 people x 4 months

Screenshot from 2024-06-11 15-30-26.png
図1.png

配線のはんだ付け検査

System overview

  A system that predicts sales of the entire store and each product by utilizing POS data of the retail business, weather information acquired from the outside, and trend information. It can also be used for past sales analysis and trend analysis.

 

Client

  Stationery sales

 

Effect after system introduction

   We were able to place orders at the right time, reduce defective inventory and missed sales, and improve profits by about 5%.

 

Technology

• Prediction engine: RNN model, LightGBM model

• Framework: Keras, Flask

• Language: Python

Development scale

  2 people x 4 months

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