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Scan AI: The Latest Advances in Artificial Intelligence for Colony Counting

As part of our ongoing efforts to improve Scan Ai’s performance, several major enhancements have been implemented to provide microbiological identification that is faster, more reliable, and better tailored to the needs of food and agricultural laboratories.

New AI-powered models now available

Rapid’ B. Cereus

The Rapid’ B. Cereus AI model is designed for the analysis of Bacillus cereus, an important indicator of microbiological quality and food safety. Through automated image analysis, it facilitates the counting and differentiation of characteristic colonies on this medium.

Easy Plate™

Scan Ai’s Easy Plate™ AI models are designed for the microbiological analysis of food samples on Easy Plate™ media.

They cover several indicators, including aerobic flora, coliforms, Escherichia coli, and staphylococci, and automate colony reading and counting for simplified interpretation.

Easy Plate AC

Easy Plate CC

Easy Plate EC

Easy Plate SA

MC-Media Pad™

With the MC-Media Pad™ AI models, Scan Ai extends reading automation to a range of microbiological analyses performed on MC-Media Pad™ media.

The available models enable the enumeration of aerobic flora, coliforms, Escherichia coli, and staphylococci, providing rapid and standardized reading of results.

MC-Media Pad
RAC

MC-Media Pad
CC

MC-Media Pad
EC/CC

MC-Media Pad
SA

These new models significantly expand the Scan Ai library and enable users to take advantage of automated recognition for a growing number of culture media used in agri-food analyses.

Scan Ai is the artificial intelligence technology integrated into Interscience’s automated counting solutions.
Using AI models trained on thousands of microbiological images, Scan Ai automatically detects, identifies, and counts colonies with high accuracy and reproducibility.

The platform is constantly evolving, with new models for new culture media added regularly, and benefits from continuous updates to its algorithms as well as to the international microbiological databases CLSI and EUCAST.

Scan Ai thus enables laboratories to save time, standardize their analyses, and improve the reliability of their results.

Updating Existing Models

Total flora
(PCA/TSA)

Enterobacteria
(VRBL/VRBG)

Escherichia coli
(TBX)

Lactobacilli
(MRS)

Staphylococci
(BAIRD-PARKER, BAIRD-PARKER RPF)

Mossel

Symphony™

Yeasts/molds
(YM agar)

Legionella
(GVPC)

Compass Bacillus cereus™

Rhapsody™

SDA

PDA

Blood Agar

Milliflex Oasis™

BioCapt™

Hycon™
contact slides

Envirocheck™
dip slide

MobIA

TSC AI

Perfecto Duo^® AI

Compass Listeria^® AI

In addition to these new integrations, several existing models have been optimized to improve:

•The accuracy of microbiological counts.
•The robustness of the algorithms in the face of sample variations.
•The reliability of results obtained on different culture media.

These improvements ensure greater reproducibility of analyses and strengthen laboratories’ confidence in the results automatically generated by Scan Ai.

Up-to-Date Microbiological Databases

Scan Ai now incorporates updates to international microbiological reference standards.

CLSI (Clinical and Laboratory Standards Institute) EUCAST (European Committee on Antimicrobial Susceptibility Testing)

Updating these databases ensures that the most recent recommendations regarding microbiological interpretation and antibiotic resistance are followed, while also ensuring greater compliance with international standards.

An increasingly effective solution

With the addition of new AI models, continuous improvements to existing algorithms, and updates to the CLSI and EUCAST databases, Scan Ai is strengthening its position as the leading tool for automating microbiological analysis.

These advancements enable laboratories to improve efficiency, standardization, and reliability while reducing the time spent on manual readings.

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Scan AI: The Latest Advances in Artificial Intelligence for Colony Counting

As part of our ongoing efforts to improve Scan Ai’s performance, several major enhancements have been implemented to provide microbiological identification that is faster, more reliable, and better tailored to the needs of food and agricultural laboratories.

New AI-powered models now available

Rapid’ B. Cereus

Easy Plate™

MC-Media Pad™

These new models significantly expand the Scan Ai library and enable users to take advantage of automated recognition for a growing number of culture media used in agri-food analyses.

Scan Ai is the artificial intelligence technology integrated into Interscience’s automated counting solutions.
Using AI models trained on thousands of microbiological images, Scan Ai automatically detects, identifies, and counts colonies with high accuracy and reproducibility.

Updating Existing Models

In addition to these new integrations, several existing models have been optimized to improve:

•The accuracy of microbiological counts.

•The robustness of the algorithms in the face of sample variations.

•The reliability of results obtained on different culture media.

These improvements ensure greater reproducibility of analyses and strengthen laboratories’ confidence in the results automatically generated by Scan Ai.

Up-to-Date Microbiological Databases

CLSI (Clinical and Laboratory Standards Institute) EUCAST (European Committee on Antimicrobial Susceptibility Testing)

An increasingly effective solution

Latest news

Scan AI: The Latest Advances in Artificial Intelligence for Colony Counting

As part of our ongoing efforts to improve Scan Ai’s performance, several major enhancements have been implemented to provide microbiological identification that is faster, more reliable, and better tailored to the needs of food and agricultural laboratories.

New AI-powered models now available

Rapid’ B. Cereus

Easy Plate™

MC-Media Pad™

These new models significantly expand the Scan Ai library and enable users to take advantage of automated recognition for a growing number of culture media used in agri-food analyses.

Scan Ai is the artificial intelligence technology integrated into Interscience’s automated counting solutions. Using AI models trained on thousands of microbiological images, Scan Ai automatically detects, identifies, and counts colonies with high accuracy and reproducibility.

Updating Existing Models

In addition to these new integrations, several existing models have been optimized to improve:

•The accuracy of microbiological counts.

•The robustness of the algorithms in the face of sample variations.

•The reliability of results obtained on different culture media.

These improvements ensure greater reproducibility of analyses and strengthen laboratories’ confidence in the results automatically generated by Scan Ai.

Up-to-Date Microbiological Databases

CLSI (Clinical and Laboratory Standards Institute) EUCAST (European Committee on Antimicrobial Susceptibility Testing)

An increasingly effective solution

Scan Ai is the artificial intelligence technology integrated into Interscience’s automated counting solutions.
Using AI models trained on thousands of microbiological images, Scan Ai automatically detects, identifies, and counts colonies with high accuracy and reproducibility.