Solution: 

 

Our Green Solutions founders David Goldstein and Yoray Halevy created an application named PotBot for use by medical cannabis users. The application is developed with a robust artificial intelligence core which aggregates and correlates peer reviewed research about specific medical indications and cannabis treatments in a HIPAA compliant manner. As users begin to sign up on the application they fill out a personal profile detailing demographic criteria and consumption habits. Upon the completion of the profile, the user is presented with a plethora of information ranging from cannabinoids that according to research could have beneficial effects on their medical indications, the most appropriate consumption method, local dispensaries and retailers, and lastly, information on physicians that could assist with medical cannabis inquiries. 

PotBot has gained significant steam from the moment it was launched. The application was covered by widely revered publications ranging from Forbes to CNBC.  While users found benefits in educating themselves for their best course of treatment, PotBot also provided data analytics encompassing demographic and consumption habits of these users. These data points are further leveraged in data packages to third party providers, such as physicians and cannabis producers, that are interested in understanding their user’s product preferences and demands. With over 100,000 users garnered in the first year since launch, PotBot has maintained steady increase in users thereby providing insights to the medical cannabis industry that was previously impossible to collect on such a grand scale. 

PotBot continuously gets smarter and provides more accurate recommendations due to its artificial intelligence core. As clinical studies and research continue to publish, PotBot verifies the authenticity and validity of the information within the study and then correlates it to current strains and cannabinoids that can provide symptom relief to each user. Given that each profile is unique, PotBot has proven to be a successful first step into providing medical cannabis users with personalized medication regimens that are geared to each user’s medical indications and consumption habits. 

 

While PotBot provides users with a hub for information regarding medical cannabis, as well as providing personalized recommendations for cannabinoid profiles and consumption methods, the data it collects is far more qualitative than quantitative. The application gathers data on user’s basic demographic information and user inputted data on their symptom relief. However, while the collected data does provide some quantitative information regarding users medical indications, age, gender, etc, it does not provide unbiased quantitative data on the consumption metrics these users utilize when consuming medical cannabis. The question became, “How can we collect data on the consumption habits of users that is both quantitative and unbiased?” The answer to that question leads us to the next case study for Our Green Solutions, RYAH dose-measuring vaporizer. 

 

OGS’ Task Overview:

 

1. Provide guidelines, scope, and project-map for building core AI functionality running on R programming language, dispensary back-ends on html-5, and customer facing app for iOS and Android. 

2. Identify leading cultivars, strains, and cultivators throughout the United States; Developing relationships with them, and attaining data on cannabinoid percentages and breakdowns.

3. Vetted and selected peer-reviewed studies that the AI engine correlated to cannabis for users to reference within the application

4. Assist in building medical advisory and advisory board. 

5. Organizing focus group testing of application to relevant target markets. 

6. Overviewing app launch and associated marketing strategy. 

7. Assisted in determining marketing budget, milestones, and vendors/partners.

8. Determine industry expos and events and aided in-booth strategy and business development. 

9. Created and designed the brand, logo, messaging, color schemes for PotBot

10. Provided de-bugging solutions during app development with a heavy focus on UX/UI in order to make user onboarding simpler

11. Communicated project management timelines to increase productivity among developers, designers, and data scientists from different regions and timezones

12. Verified testing compliance of strains inputted into the application to ensure proper recommendation processes

13. Guided the company through the steps needed for application approval via Apple App Store & Google Play Store

14. Created in-store promotions and educated brand ambassadors on how to assist users in downloading and using the application