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Can AI Create a Cannabis Grading System?

The freshness of the legal cannabis industry means that it’s always evolving and growing. One business is working on the next evolution in cannabis grading.

Keirton, a product development firm that makes technology for the cannabis industry, has developed an automated system that utilizes artificial intelligence (AI) to determine not only the potency of cannabis but to visually grade it. According to Jay Evans, CEO of Keirton, it may even be able to smell cannabis soon.

This innovation was born out of the need for a better way to test the quality of cannabis and get consistent results.

“One thing that is apparent in the new cannabis industry is that there is a lot of inconsistency in what is deemed quality,” Evans says. “Right now LPs are using potency, which can create big challenges.”

Evans suggests that a better option might be the grading system used in the illicit market, which uses A to AAAAA to denote the quality of a bud based on potency as well as smell, taste, appearance, and effects.

Once the rest of the world gets involved in the cannabis trade, a consistent grading system will become even more important. To purchase cannabis from a country half-way around the world, the buyer has to rely on the experience of a middleman.

If a universal system was implemented, it would be much easier to trust the quality of the product.

That sounds great, in theory, but how could something like that be implemented?

According to Evans, it would simply be added to the already existing automation process. Keirton has developed software using AI, complete with vision systems and “essentially sniffers” that would determine the potency and the visual score of cannabis, then give it a grade. The piece de resistance is the AI, which adapts and learns more with each batch of buds sent through.

Ideally, producers could grade their own cannabis and gain a myriad of insights for themselves and their consumers. This automation system could give LPs a better understanding of the quality of their cannabis compared to other producers and give them a leg up on troubleshooting issues with their crops. On top of that, the system would help filter out imperfections and inconsistencies.

With a product that easily lends itself to inconsistencies based on growing conditions, automation with a system like this could make sure customers always know what they are going to get.

“Automation is consistent, and any good brand has consistency,” says Evans.