Proprietary algorithms and machine learning together with standardized processes.

Our in-field grading application was developed by a group of experienced cannabis experts who are passionate about qualitative metrics and efficient quality verification. We are dedicated to serving the industry by providing trust and transparency through accurate, first hand, and real-time data collection.

Certified grading specialists use our app to gather qualitative and quantitative data while physically inspecting each and every lot. During this physical inspection, material is scrutinized using the ICHS' 100-point grading scale and once done, material is standardized and ready for purchase or sale on the open market.

With more than 1,000,000 qualitative data points, 500,000 transactional data points and 300,000 pounds of cannabis graded, we have plenty of data to get started. With every gram, pound and harvest that goes by, our data model is constantly improving with an ever expanding set of weights and biases. What does this mean and why does it matter? Utilizing AI and machine learning algorithms, our appraisal reports, Certificate of Grade and data insights will be getting more accurate and precise every single day.

Utilizing millions of monthly grading records, transactional data and market trends, our real-time insights are the most accurate and truest-to-reality picture of the bulk wholesale cannabis supply chain. Comparisons of +100 product categories of plant material with appraisal, grade and sales, through a qualitative lens, provides invaluable data to any serious stakeholder in this burgeoning industry. Without our real-time insights, one could say you're driving blind.

Utilizing real world data and historical grading information, we developed and employed proprietary algorithms that allow our technology to appraise, grade and certify material accurately and efficiently, based on current market conditions and real-time transactional information compared against qualitative and qualitative product information down to the lot, and gram.