PotBotics' engine that drives all of the products in our pipeline was developed with the future in mind. In order to bring the cannabis industry from a tiny seed to a budding flower, PotBotics developed a Cloud infrastructure that is built using artificial intelligence, Natural Language Processing, and the highest security standards.
Overview of cloud data
The PotBotics Cloud aggregates and correlates all of the data gathered by the PotBotics product suite. Hosted on the Amazon web services, the PotBotics cloud is the first cannabis-based HIPAA compliant storing location that is built using artificial intelligence... The data that is stored on the cloud is correlated with all peer-reviewed studies on cannabis from across the globe, creating valuable insights that propel the industry forward. This graph reasoning engine allows us to answer fundamental questions about the future of cannabis as a medicine.
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With just a few clicks, the dashboard can answer many elusive questions such as:
- What are the most frequently mentioned cannabinoids?
- What are the cannabinoids, active on a given disease, which have also been shown to be active on other diseases by the recent publications?
- What are the most searched topics/classes?
- What are the latest mentions about cannabinoids which have been used to treat the particular disease and by which doctors?
- What are the most mentioned diseases treated by particular strain in the past year?
PotBotics has developed a robust Artificial Intelligence Engine focused around a technology called Graph Reasoning. The Artificial Intelligence engine analyzes correlations to understand the complex relationships found in peer reviewed research, consumer feedback, and medical cannabis.
Our proprietary method creates the largest knowledge graph in the medical marijuana industry comprised of:
- Correlated peer reviewed studies from across the globe
- Lab research of cannabinoid and terpene data
- Patient demographics, medical indications, and consumption habits
The PotBotics NLP Pipeline tool for extracting valuable data from medical, and clinical, sources in order to make the data ready for analysis. It's user interface makes exploring data easy and allows for deeper analysis of correlations between data entities.
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