Fresh Scanner

A platform for automating of quality control and categorization of fruits and vegetables with reports.

Our customer is a top manager of one of the largest Russian retailers. He wanted us to create a solution with the following characteristics:

Laboratory for digitizing the results of the product examination.
Databases with the results of examinations conducted in accordance with the standards of the United Nations Economic Commission for Europe (UNECE) and the Organization for Economic Cooperation and Development (OECD).
Artificial intelligence based on trained neural network algorithms for assessing the quality of fresh fruits and vegetables.
Software for managing the implementation of the full cycle business process including analysis of products, shipment, and statistics.

6 team members including 3 software developers

80k USD Budget

Revolutionary technology applied

The use of advanced developments in the field of image analysis using:

01

Convolutional neural networks, industrial applications (RetinaNET, G-NET, MASK-KST)

02

Canon cameras used in the scanner.

03

Sets of libraries and frameworks, such as Rutogsh + Fast.ai.

Result

The project is still at the “pre-MVP stage”. These are the achievements which have been already integrated into one platform so far:

A scanner for obtaining high-quality photographs has been developed.
A unit of trade professionals has been formed to assess the quality of fruits and vegetables.
Data collection for machine learning is ongoing.
Developed software to assess the quality of fruits and vegetables.
The virtual personal Cabinet of the expert-receiver has been developed.
The automated process of forming reports has been developed.

We were approached by the client,wanting us to solve his product quality control issue. Once we had a clear understanding of what our client wanted to achieve, an action plan was developed.

01

Proof of
Concept

(3Q 2018- 4Q 2018)

After consulting with the industry professionals the technology stack was selected and the timeframe worked out. Project costs were calculated.
We developed the brand identity.
We registered a company under the name ”Neirofresh”.
We supplied the startup company with Programming professionals
A prototype of a scanner successfully constructed and tested together with our custom software.

02

MVP

(4Q 2018 - 3Q 2019)

During the preparations for the release of the MVP additional tests conducted.
The product achieved an accuracy of 96% for the quality category, 43% for defects.
MVP soon to be ready.
Agreement for further development of the product successfully signed after the latest tests.
Company applied for $100k grant.

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Email: info@cb.technology

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