AI Use Cases in Food and Drug Administration

Introduction

The Food and Drug Administration (FDA) is harnessing the power of artificial intelligence (AI) across various initiatives to advance its mission of ensuring public health and safety. According to AlphaSense, “With a total addressable market of nearly $50 billion for AI-enabled drug development, it is estimated that 30% of new drugs will be discovered using AI by 2025.” AI technologies are being utilized to enhance predictive modeling for pest detection, automate the analysis of agricultural and environmental data, and improve the management of food and nutrition information. From predicting invasive pest species at ports of entry to detecting early signs of disease in crops and optimizing resource allocation in agriculture, the below use cases highlight the FDA’s commitment to leveraging cutting-edge technologies for more effective and efficient operations.

Use Cases

  • 1. Predictive modeling of invasive pest species and category at the port of entry using machine learning algorithms

    The Food and Drug Administration (FDA) is employing machine learning algorithms to enhance the predictive modeling of invasive pest species at ports of entry. By analyzing inspection data, this initiative aims to improve the detection capabilities for significant invasive and quarantine pests, thereby strengthening biosecurity measures and protecting agricultural resources.

  • 2. Detection of pre-symptomatic HLB infected citrus

    This project focuses on the detection of pre-symptomatic Huanglongbing (HLB) infection in citrus crops by analyzing multispectral and thermal imagery. The goal is to identify specific pixels that exhibit HLB infection signatures, enabling early intervention and management strategies to mitigate the spread of this devastating disease in citrus orchards.

  • 3. High throughput phenotyping in citrus orchards

    The High Throughput Phenotyping project aims to enhance the monitoring of citrus orchard health by automating the processes of locating, counting, and categorizing citrus trees. This initiative utilizes advanced imaging and data analysis techniques to provide timely insights into orchard conditions, facilitating better management practices and improving overall crop health.

  • 4. Detection of aquatic weeds

    This project focuses on the identification and localization of aquatic weeds using advanced detection techniques. By accurately mapping the presence of these invasive species, the initiative aims to support effective management and control strategies to protect aquatic ecosystems and maintain biodiversity.

  • 5. Automated Detection & Mapping of Host Plants from Ground Level Imagery

    The Automated Detection & Mapping of Host Plants project focuses on utilizing ground-level imagery, such as street view photos, to generate detailed maps of target tree species. This initiative aims to enhance the understanding of plant distributions and support ecological studies and management efforts by providing accurate spatial data on host plants.

  • 6. Standardization of cut flower business names for message set data

    The Standardization of Cut Flower Business Names project employs natural language processing (NLP) techniques to standardize business names in message set data. The process involves cleaning the data by removing punctuation and calculating cosine similarity to match similar terms. This standardization enhances data consistency and facilitates better data analysis and reporting within the cut flower industry.

  • 7. Approximate string or fuzzy matching, used to automate matching similar, but not identical, text in administrative documents

    The Approximate String or Fuzzy Matching project utilizes an algorithm to compute string similarity metrics, enabling the classification of similar but not identical text in administrative documents. This automation reduces information duplication and minimizes the need for manual error-checking, streamlining document management processes and improving data accuracy.

  • 8. Training machine learning models to automatically read file attachments and save information into a more convenient Excel format.

    This project focuses on training machine learning models to automate the reading of file attachments, specifically PDF documents, and extract relevant information into a more user-friendly Excel format. By leveraging artificial intelligence, the initiative aims to save program managers time and effort, as they often receive numerous documents daily and need to extract specific data from them efficiently.

  • 9. Artificial Intelligence for correlative statistical analysis

    The Artificial Intelligence for Correlative Statistical Analysis project employs various AI-driven statistical techniques to model predictive relationships between different variables. Commonly used methods include random forests, artificial neural networks, k-nearest neighbor clustering, and support vector machines. This initiative enhances the FDA’s ability to make data-driven predictions and informed decisions based on complex datasets.

  • 10. ARS Project Mapping

    The ARS Project Mapping initiative utilizes natural language processing (NLP) to analyze research project plans, performing term analysis and clustering. This approach allows national program leaders to interact with a dashboard that highlights synergies and patterns across various Agricultural Research Service (ARS) research program portfolios, facilitating better collaboration and resource allocation.

  • 11. NAL Automated indexing

    The NAL Automated Indexing project employs Cogito software to automate the subject indexing of approximately 500,000 peer-reviewed journal articles annually. By utilizing the National Ag Library Thesaurus (NALT) concept space, the software annotates articles with relevant metadata, enhancing the discoverability of content in the Library’s bibliographic citation databases, including AGRICOLA, PubAg, and Ag Data Commons.

  • 12. Democratizing Data

    The Democratizing Data project aims to leverage AI tools, machine learning, and natural language processing to analyze how publicly funded data and evidence are utilized to benefit science and society. By understanding these dynamics, the initiative seeks to promote transparency, accessibility, and effective use of data in public health and policy-making.

  • 13. Westat

    The Westat project is a competitive initiative aimed at discovering automated methods to effectively link USDA nutrition information to a dataset containing 750,000 food items related to purchases and acquisitions. Competing teams employed various AI techniques, including natural language processing (NLP), random forests, and semantic matching, to develop innovative solutions that enhance the integration of nutrition data with food item information, ultimately supporting better dietary guidance and public health initiatives.

  • 14. Retailer Receipt Analysis

    The Retailer Receipt Analysis project is a proof of concept that employs Optical Character Recognition (OCR) technology to analyze a sample of up to 1,000 Food and Nutrition Service (FNS) receipts and invoices. This initiative aims to demonstrate how the current manual review process can be automated, leading to significant time savings for staff, improved accuracy in reviews, and enhanced detection of complex patterns. The ultimate goal is to develop a review system that features an automated workflow capable of learning from analyst feedback, incorporating known Supplemental Nutrition Assistance Program (SNAP) fraud patterns, identifying new patterns, and visualizing alerts related to these patterns on retailer invoices and receipts.

  • 15. Nutrition Education & Local Access Dashboard

    The Nutrition Education & Local Access Dashboard aims to create a comprehensive county-level visualization of nutrition support provided by the Food and Nutrition Service (FNS). This dashboard focuses on nutrition education and local food access, integrating various metrics related to hunger and nutritional health. To enhance usability, the team developed a K-means clustering script that categorizes states into seven different groups based on characteristics such as Farm to School intensity, program activity, ethnicity, fresh food access, school size, and program participation. This clustering enables users to identify similar states, fostering potential partnerships and collaborations that may not have been previously considered.

  • 16. Land Change Analysis Tool (LCAT)

    The Land Change Analysis Tool (LCAT) utilizes a random forest machine learning classifier to create high-resolution land cover maps derived from aerial and satellite imagery. Training data for the model is generated through a custom-built web application, and the processing tasks are executed on a 192-node Docker cluster to efficiently handle CPU-intensive computations. The results of this analysis are made publicly available through an image service. To date, the project has successfully mapped over 600 million acres and generated more than 700,000 training samples, contributing valuable data for land management and environmental monitoring.

  • 17. Ecosystem Management Decision Support System (EMDS)

    The Ecosystem Management Decision Support System (EMDS) is a spatial decision support tool designed for landscape analysis and planning. It operates as a component of popular geographic information systems (GIS) such as ArcGIS and QGIS. Users can develop tailored applications to address specific challenges, utilizing a combination of four AI engines: logic processing, multi-criteria decision analysis, Bayesian networks, and Prolog-based decision trees. This flexibility allows for comprehensive analysis and informed decision-making in ecosystem management.

  • 18. Wildland Urban Interface - Mapping Wildfire Loss

    The Wildland Urban Interface – Mapping Wildfire Loss project is a proof-of-concept study that explores the application of machine learning techniques, specifically deep learning and convolutional neural networks, along with object-based image classification methods. The goal is to accurately identify buildings, assess building loss, and evaluate defensible space around structures before and after wildfire events in areas where urban and wildland environments intersect. This research aims to enhance understanding of wildfire impacts and inform mitigation strategies.

  • 19. CLT Knowledge Database

    The CLT Knowledge Database is an information system designed to catalog and provide access to cross-laminated timber (CLT) information. It utilizes data aggregator bots that scour the internet for relevant content, searching for hundreds of keywords and employing machine learning to assess the relevance of the findings. The search engine intelligently locates and updates pertinent CLT references, categorizing information based on common applications and interest areas. As of February 24, 2022, the database has cataloged over 3,600 publications related to various aspects of CLT. This system promotes the growth of mass timber markets by disseminating knowledge, facilitating collaboration among stakeholders, and minimizing duplication of efforts. It benefits manufacturers, researchers, design professionals, code officials, government agencies, and other stakeholders, ultimately supporting the increased use of mass timber and enhancing forest health by raising the economic value of forests.

  • 20. RMRS Raster Utility

    The RMRS Raster Utility is a .NET object-oriented library designed to streamline data acquisition, raster sampling, and both statistical and spatial modeling. This utility aims to reduce the processing time and storage space required for raster analysis, making it more efficient for users. Additionally, the library incorporates machine learning techniques, enhancing its capabilities for analyzing and interpreting raster data in various applications.

  • 21. TreeMap 2016

    TreeMap 2016 is a comprehensive tree-level model that represents the forests of the contiguous United States. It integrates forest plot data from the Forest Inventory and Analysis (FIA) program and aligns this data with a 30×30 meter grid. The model is utilized in both private and public sectors for various applications, including fuel treatment planning, snag hazard mapping, and estimating terrestrial carbon resources. A random forests machine learning algorithm was employed to impute forest plot data into a set of target rasters provided by the Landscape Fire and Resource Management Planning Tools (LANDFIRE). The model considers various predictor variables, including forest cover percentage, tree height, vegetation type, topography (slope, elevation, aspect), geographical location (latitude and longitude), biophysical factors (photosynthetically active radiation, precipitation, temperature variations, relative humidity, and vapor pressure deficit), and disturbance history (time since disturbance and type of disturbance) for the landscape as of 2016.

  • 22. Landscape Change Monitoring System (LCMS)

    The Landscape Change Monitoring System (LCMS) is a national initiative that utilizes remote sensing data from Landsat and Sentinel satellites, produced by the USDA Forest Service, to map and monitor changes in vegetation canopy cover, land cover, and land use. The system employs temporal change classifications in conjunction with training data to conduct supervised classification processes, enabling the identification of vegetation gain and loss as well as changes in land cover and use. This monitoring system provides valuable insights for land management and conservation efforts.

  • 23. Geospatial and Remote Sensing Training Courses

    The Geospatial and Remote Sensing Training Courses provide education on various software and scripting techniques that facilitate machine learning applications in geospatial analysis. The curriculum is dynamic, covering topics such as introductory and advanced change detection, the eCognition software package, and geospatial scripting for Google Earth Engine. Additionally, some courses include training on using Collect Earth Online, equipping participants with the skills needed to analyze and interpret remote sensing data effectively.

  • 24. Forest Health Detection Monitoring

    The Forest Health Detection Monitoring project employs machine learning models to enhance the analysis of forest health across the United States. This involves upscaling training data collected from various sources, including Sentinel-2, Landsat, MODIS, and lidar imagery, to effectively map and monitor stages of forest mortality and defoliation. Additionally, the project includes post-processing of raster outputs into vector polygons, facilitating more detailed spatial analysis and visualization of forest health conditions.

  • 25. Cropland Data Layer

    The Cropland Data Layer (CDL) project utilizes machine learning algorithms to analyze satellite sensor readings and classify the type of crop or agricultural activity present in each 30 square meter pixel on the ground. The algorithms are trained using data from the USDA’s Farm Services Agency and other reliable sources to establish “ground truth.” This process not only generates accurate classifications but also allows for the assessment of classification accuracy. The CDL has been produced for national coverage since 2008 and is particularly accurate for major commodities like corn and soybeans. Additional information and background on the CDL can be found in various peer-reviewed research papers and presentations.

  • 26. List Frame Deadwood Identification

    The List Frame Deadwood Identification project employs boosted regression trees to analyze various inputs, including administrative linkage data, frame data, and historical response information. The model generates a propensity score that indicates the relative likelihood of a farm operation being out of business. By identifying common tree splits and integrating expert knowledge, the project aims to establish a systematic process for identifying and addressing deadwood in agricultural operations, thereby improving data accuracy and resource allocation.

  • 27. Census of Agriculture Response Propensity Scores

    The Census of Agriculture Response Propensity Scores project utilizes random forest models to derive scores that predict the likelihood of response to the Census of Agriculture (COA). By analyzing historical data, control data, and other survey information, these scores assist in targeting more effective data collection strategies. This approach enhances the efficiency of the census process by focusing efforts on areas with higher predicted response rates.

  • 28. Climate Change Classification NLP

    The Climate Change Classification NLP project employs natural language processing techniques to classify projects funded by the National Institute of Food and Agriculture (NIFA) as either related to climate change or not. The model analyzes input features such as project titles, non-technical summaries, objectives, and keywords. The classification results in a binary outcome, indicating whether each project is associated with climate change, thereby aiding in the assessment of funding priorities and research focus areas.

  • 29. Operational water supply forecasting for western US rivers

    The Operational Water Supply Forecasting project for western U.S. rivers relies on forecasts of spring-summer river flow volumes generated by operational hydrologic models. The USDA Natural Resources Conservation Service (NRCS) National Water and Climate Center operates the largest regional forecasting system, continuing a nearly century-old tradition. Recently, the NWCC developed a next-generation prototype called the multi-model machine-learning metasystem (M4), which integrates various AI and data science technologies tailored to meet specific user needs. The system requires inputs related to snow and precipitation from the NRCS Snow Survey and Water Supply Forecast program’s SNOTEL environmental monitoring network, although it is adaptable. In hindcasting tests across diverse environments in the western U.S. and Alaska, the M4 system demonstrated significant improvements in out-of-sample accuracy compared to existing benchmarks. Key technical features, such as multi-model ensemble modeling, autonomous machine learning (AutoML), hyperparameter pre-calibration, and theory-guided data science, enable automated training and operation. Live operational testing at selected sites has confirmed the logistical feasibility of workflows and provided geophysical explanations of results based on known hydroclimatic processes, addressing concerns about the opacity of machine learning models and allowing for relatable forecast narratives for NRCS customers.

  • 30. Ecological Site Descriptions (machine learning)

    The Ecological Site Descriptions project involves the analysis of over 20 million records related to soil data and 20,000 text documents containing information on ecological states and transitions. This extensive analysis aims to enhance understanding of ecological conditions and inform land management practices by leveraging machine learning techniques to extract insights from the vast dataset.

  • 31. Conservation Effects Assessment Project

    The Conservation Effects Assessment Project aims to predict the conservation benefits achieved at the field level through various agricultural practices. The model integrates data from farmer surveys, APEX modeling results, and environmental data to assess the effectiveness of conservation efforts. This predictive capability supports informed decision-making and resource allocation for conservation initiatives.

  • 32. Digital Imagery (no-change) for NRI program

    The Digital Imagery (No-Change) project for the National Resources Inventory (NRI) program employs neural networks and other artificial intelligence technologies to identify areas in digital imagery that have not changed over time. This capability is crucial for monitoring land use and resource conditions, enabling efficient management of natural resources and supporting the goals of the NRI program.

  • 33. Artificial Intelligence SPAM Mitigation Project

    The Artificial Intelligence SPAM Mitigation Project utilizes a combination of Robotic Process Automation (RPA) and machine learning (AI/ML) models to automatically identify and eliminate spam and marketing emails from civil rights complaints email channels. Given that a substantial portion of incoming emails to the Office of Adjudication and Special Counsel Review (OASCR) consists of spam, marketing, and phishing attempts, this solution aims to enhance the efficiency and security of email management within the department.

  • 34. Acquisition Approval Request Compliance Tool

    The Acquisition Approval Request Compliance Tool employs a natural language processing (NLP) model to analyze procurement header and line descriptions within the USDA’s Integrated Acquisition System (IAS). This model assesses the likelihood that a given award is related to information technology (IT) and may therefore require an Acquisition Approval Request (AAR). By examining the text characteristics of awards with existing AAR numbers, the model calculates the probability for procurements lacking an AAR number, thereby streamlining compliance processes and enhancing procurement accuracy.

  • 35. Intelligent Ticket Routing

    The Intelligent Ticket Routing project automates the process of routing BMC Remedy tickets to the appropriate work groups. Utilizing a combination of technologies, including Python, JupyterHub, Scikit-learn, GitLab, Flask, Gunicorn, Nginx, and ERMS, this system enhances operational efficiency by ensuring that tickets are directed to the right teams without manual intervention, thereby improving response times and service quality.

  • 36. Predictive Maintenance Impacts

    The Predictive Maintenance Impacts project focuses on forecasting the effects of maintenance activities on infrastructure items within the DISC framework. By leveraging tools such as Einblick, MySQL, Python, Linux, and Tableau, the project aims to analyze maintenance data and predict potential impacts, enabling proactive maintenance strategies that enhance infrastructure reliability and performance.

  • 37. Video Surveillance System

    The Video Surveillance System (VSS) is designed to provide comprehensive video management capabilities, integrating various surveillance subsystems, including NVRs, DVRs, encoders, fixed and pan-tilt cameras, network switches, routers, and other necessary hardware. The VSS will enable the collection, management, and clear presentation of video feeds from multiple sources, facilitating a unified configuration platform for both analog and digital video devices. This system normalizes disparate video systems into a cohesive viewing experience, allowing operators to easily drag and drop cameras into views and utilize advanced features for tracking targets across sequential cameras, enhancing overall security management.

Conclusion

The FDA's adoption of AI and Machine Learning for Drug Discovery represents a transformative shift towards more efficient and effective management of public health, agricultural resources, and environmental monitoring. By integrating advanced predictive models, automation, and data analytics, the FDA is enhancing its capability to address challenges ranging from pest detection and disease management to optimizing food and nutrition data. These AI-driven initiatives not only streamline processes but also provide deeper insights and more accurate predictions, ultimately supporting the FDA's mission to protect public health and ensure safety across various domains. Through these advancements, the FDA is setting a precedent for leveraging technology to meet complex challenges and drive forward-looking solutions in its regulatory and research efforts.

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    If you are based in Colorado, please visit this website to file a complaint. If you are based in Virginia, please visit this website to file a complaint. If you are based in Connecticut, please visit this website to file a complaint.

    File a Complaint (GDPR Article 77, LGPD, POPIA)

    You have the right to bring a claim before their competent data protection authority. If you are based in the EEA, please visit this website (http://ec.europa.eu/newsroom/article29/document.cfm?action=display&doc_id=50061) for a list of local data protection authorities.

    Withdrawing Consent

    If you have consented to our processing of your Personal Data, you have the right to withdraw your consent at any time, free of charge, such as where you wish to opt out from marketing messages that you receive from us. If you wish to withdraw your consent, please contact us using the information found at the bottom of this page.

    How to Exercise Your Rights

    You can make a request to exercise any of these rights in relation to your Personal Data by sending the request to our privacy team by using the form below.
    For your own privacy and security, at our discretion, we may require you to prove your identity before providing the requested information.

    Changes

    We may modify this Policy at any time. If we make changes to this Policy then we will post an updated version of this Policy at this website. When using our services, you will be asked to review and accept our Privacy Policy. In this manner, we may record your acceptance and notify you of any future changes to this Policy.

    Contact Us

    To request a copy for your information, unsubscribe from our email list, request for your data to be deleted, or ask a question about your data privacy, we've made the process simple:

    Email us

    Terms and Conditions

    Our aim is to keep this Agreement as readable as possible, but in some cases for legal reasons, some of the language is required "legalese".

    Your Acceptance of This Agreement

    These terms of service are entered into by and between You and Scry Analytics, Inc., ("Company," "we," "our," or "us"). The following terms and conditions, together with any documents they expressly incorporate by reference (collectively "Terms of Service"), govern your access to and use of www.scryai.com, including any content, functionality, and services offered on or through www.scryai.com (the "Website").

    Please read the Terms of Service carefully before you start to use the Website.

    By using the Website [or by clicking to accept or agree to the Terms of Service when this option is made available to you], you accept and agree to be bound and abide by these Terms of Service and our Privacy Policy, found at Privacy Policy, incorporated herein by reference. If you do not want to agree to these Terms of Service, you must not access or use the Website.

    By accessing and using this website, You accept and:

    Accept and agree to be bound and comply with these terms of service. You represent and warrant that you are the legal age of majority under applicable law to form a binding contract with us and, you agree if you access the website from a jurisdiction where it is not permitted, you do so at your own risk.

    Updates to Terms of Service

    We may revise and update these Terms of Service from time to time in our sole discretion. All changes are effective immediately when we post them and apply to all access to and use of the Website thereafter.

    Continuing to use the Website following the posting of revised Terms of Service means that you accept and agree to the changes. You are expected to check this page each time you access this Website so you are aware of any changes, as they are binding on you.

    Your Responsibilities

    You are required to ensure that all persons who access the Website are aware of this Agreement and comply with it. It is a condition of your use of the Website that all the information you provide on the Website is correct, current, and complete.

    You are solely and entirely responsible for your use of the website and your computer, internet and data security.

    Prohibited Activities

    You may use the Website only for lawful purposes and in accordance with these Terms of Service. You agree not to use the Website:

    • In any way that violates any applicable federal, state, local or international law or regulation (including, without limitation, any laws regarding the exports of data software to and from the U.S. or other countries).
    • For the purpose of exploiting, harming, or attempting to exploit or harm minors in any way by exposing them to inappropriate content, asking for personally identifiable information or otherwise.
    • To send, knowingly receive, upload, download, use, or re-use any material that does not comply with the Submission Standards set out in these Terms of Service.
    • To transmit, or procure the sending of, any advertising or promotional material, including any "junk mail," "chain letter," "spam," or any other similar solicitation.
    • To impersonate or attempt to impersonate the Company, a Company employee, another user, or any other persona or entity (including, without limitation, by using email addresses associated with any of the foregoing).
    • To engage in any other conduct that restricts or inhibits anyone's use or enjoyment of the website, or which as determined by us, may harm the Company or users of the website, or expose them to liability.

    Additionally, you agree not to:

    • Use the Website in any manner that could disable, overburden, damage, or impair the site or interfere with any other party's use of the Website, including their ability to engage in real-time activities through the Website.
    • Use any robot, spider, or other automatic device, process, or means to access the Website for any purpose, including monitoring or copying any of the material on the Website.
    • Use any manual process to monitor or copy any of the material on the Website, or for any other purpose not expressly authorized in these Terms of Service, without our prior written consent.
    • Use any device, software, or routine that interferes with the proper working of the Website.
    • Introduce any viruses, Trojan horses, worms, logic bombs, or other material that is malicious or technologically harmful.
    • Attempt to gain unauthorized access to, interfere with, damage, or disrupt any parts of the Website, the server on which the Website is stored, or any server, computer, or database connected to the Website.
    • Attack the Website via a denial-of-service attack or a distributed denial-of-service attack.
    • Otherwise attempting to interfere with the proper working of the Website.

    Intellectual Property Rights

    The Website and its entire contents, features, and functionality (including but not limited to all information, software, text, displays, images, video, and audio, and the design, selection, and arrangement thereof) are owned by the Company, its licensors, or other providers of such material and are protected by United States and international copyright, trademark, patent, trade secret, and other intellectual property or proprietary rights laws.

    These Terms of Service permit you to use the Website for your personal, non-commercial use only. You must not reproduce, distribute, modify, create derivative works of, publicly display, publicly perform, republish, download, store, or transmit any of the material on our Website, except as follows:

    • Your computer may temporarily store copies of such material in RAM incidental to your accessing and viewing those materials.
    • You may store files that are automatically cached by your Web browser for display enhancement purposes.
    • You may print or download one copy of a reasonable number of pages of the Website for your own personal, non-commercial use and not for further reproduction, publication or distribution.
    • If we provide social media features with certain content, you may take such actions as are enabled by such features.

    You must not:

    • Modify copies of any materials from this site.
    • Delete or alter any of the copyright, trademark, or other proprietary rights notices from copies of materials from this site.

    You must not access or use for any commercial purposes any part of the website or any services or materials available through the Website.

    If you print, copy, modify, download, or otherwise use or provide any other person with access to any part of the Website in breach of the Terms of Service, your right to use the Website will stop immediately and you must, at our option, return or destroy any copies of the materials you have made. No right, title, or interest in or to the Website or any content on the Website is transferred to you, and all rights not expressly granted are reserved by the Company. Any use of the Website not expressly permitted by these Terms of Service is a breach of these Terms of Service and may violate copyright, trademark, and other laws.

    User Submissions and Submission Standards

    The Website may provide you with the opportunity to create, submit, post, display, transmit, public, distribute, or broadcast content and materials to us or in the Website, including but not limited to text, writings, video, audio, photographs, graphics, comments, ratings, reviews, feedback, or personal information or other material (collectively, "Content"). You are responsible for your use of the Website and for any content you provide, including compliance with applicable laws, rules, and regulations.

    All User Submissions must comply with the Submission Standards and Prohibited Activities set out in these Terms of Service.

    Any User Submissions you post to the Website will be considered non-confidential and non-proprietary. By submitting, posting, or displaying content on or through the Website, you grant us a worldwide, non-exclusive, royalty-free license to use, copy, reproduce, process, disclose, adapt, modify, publish, transmit, display and distribute such Content for any purpose, commercial advertising, or otherwise, and to prepare derivative works of, or incorporate in other works, such as Content, and grant and authorize sublicenses of the foregoing. The use and distribution may occur in any media format and through any media channels.

    You represent and warrant that:

    • You own or control all rights in and to the User Submissions and have the right to grant the license granted above to us and our affiliates and service providers, and each of their and our respective licensees, successors, and assigns.
    • All of your User Submissions comply with these Terms of Service.

    We do not assert any ownership over your Content. You retain full ownership of all of your Content and any intellectual property rights or other proprietary rights associated with your Content. We are not liable for any statement or representations in your Content provided by you in any area in the Website. You are solely responsible for your Content related to the Website and you expressly agree to exonerate us from any and all responsibility and to refrain from any legal action against us regarding your Content. We are not responsible or liable to any third party for the content or accuracy of any User Submissions posted by you or any other user of the Website. User Submissions are not endorsed by us and do not necessarily represent our opinions or the view of any of our affiliates or partners. We do not assume liability for any User Submission or for any claims, liabilities, or losses resulting from any review.

    We have the right, in our sole and absolute discretion, (1) to edit, redact, or otherwise change any Content; (2) to recategorize any Content to place them in more appropriate locations in the Website; and (3) to prescreen or delete any Content at any time and for any reason, without notice. We have no obligation to monitor your Content. Any use of the Website in violation of these Terms of Service may result in, among other things, termination or suspension of your right to use the Website.

    These Submission Standards apply to any and all User Submissions. User Submissions must in their entirety comply with all the applicable federal, state, local, and international laws and regulations. Without limiting the foregoing, User Submissions must not:

    • Contain any material that is defamatory, obscene, indecent, abusive, offensive, misleading, harassing, violent, hateful, inflammatory, or otherwise objectionable.
    • Promote sexually explicit or pornographic material, violence, or discrimination based on race, sex, religion, nationality, disability, sexual orientation, or age.
    • Infringe any patent, trademark, trade secret, copyright, or other intellectual property or other rights of any other person.
    • Violate the legal rights of others or contain any material that could give rise to any civil or criminal liability under applicable laws or regulations or that otherwise may be in conflict with these terms of service and our Privacy Policy.
    • Be likely to deceive any person.
    • Promote any illegal activity, or advocate, promote, or assist in any unlawful act.
    • Cause annoyance, inconvenience, or needless anxiety or be likely to upset, embarrass, alarm, or annoy any other person.
    • Impersonate any person, or misrepresent your identity or affiliation with any person or organization.
    • Involve commercial activities or sales, such as contests, sweepstakes, and other sales promotions, barter, or advertising.
    • Give the impression that they emanate from or are endorsed by us or any other person or entity, if this is not the case.

    Our Rights

    We have the right, without provision of notice to:

    • Remove or refuse to post any User Submission for any or no reason in our sole discretion;
    • Take any action with respect to any User Submission that we deem necessary or appropriate in our sole discretion, including if we believe that such User Submission violates the Terms of Service, including the Submission Standards, infringes any intellectual property right or other right of any person or entity, threatens the personal safety of users of the Website or the public, or could create liability for the Company;
    • Take appropriate legal action, including, without limitation, referral to or cooperation with law enforcement or regulatory authorities, or notifying the harmed party of any illegal or unauthorized use of the Website; and
    • Terminate or suspend your access to all or part of the Website for any or no reason, including, without limitation, any violation of these Terms of Service.

    You waive and hold harmless company and its parent, subsidiaries, affiliates, and their respective directors, officers, employees, agents, service providers, contractors, licensors, licensees, suppliers, and successors from any and all claims resulting from any action taken by the company and any of the foregoing parties relating to any, investigations by either the company or by law enforcement authorities.

    Third Party Links and Sites

    For your convenience, this Website may provide links or pointers to third-party sites or third-party content. We make no representations about any other websites or third-party content that may be accessed from this Website. If you choose to access any such sites, you do so at your own risk. We have no control over the third-party content or any such third-party sites and accept no responsibility for such sites or for any loss or damage that may arise from your use of them. You are subject to any terms and conditions of such third-party sites.

    Social Media Features

    This Website may provide certain social media features that enable you to:

    • Link from your own or certain third-party websites to certain content on this Website.
    • Send emails or other communications with certain content, or links to certain content, on this Website.
    • Cause limited portions of content on this Website to be displayed or appear to be displayed on your own or certain third-party websites.

    You may use these features solely as they are provided by us and solely with respect to the content they are displayed with. Subject to the foregoing, you must not:

    • Establish a link from any website that is not owned by you.
    • Cause the Website or portions of it to be displayed on, or appear to be displayed by, any other site, for example, framing, deep linking, or in-line linking.
    • Link to any part of the Website other than the homepage.
    • Otherwise take any action with respect to the materials on this Website that is inconsistent with any other provision of these Terms of Use.

    The Website from which you are linking, or on which you make certain content accessible, must comply in all respects with the Submission Standards set out in these Terms of Service.

    You agree to cooperate with us in causing any unauthorized framing or linking immediately to stop.
    We reserve the right to withdraw linking permission without notice.
    We may disable all or any social media features and any links at any time without notice in our discretion.

    Disclaimers, Liability and Indemnification

    You understand and agree that your use of the website, its content, and any goods, digital products, services, information or items found or attained through the website is at your own risk. The website, its content, and any goods, services, digital products, information or items found or attained through the website are provided on an "as is" and "as available" basis, without any warranties or conditions of any kind, either express or implied including, but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The foregoing does not affect any warranties that cannot be excluded or limited under applicable law.

    You acknowledge and agree that company or its respective directors, officers, employees, agents, service providers, contractors, licensors, licensees, suppliers, or successors make no warranty, representation, or endorsement with respect to the completeness, security, reliability, suitability, accuracy, currency, or availability of the website or its contents or that any goods, services, digital products, information or items found or attained through the website will be accurate, reliable, error-free, or uninterrupted, that defects will be corrected, that our website or the server that makes it available or content are free of viruses or other harmful components or destructive code.

    How We Limit Our Liability to You

    Except where such exclusions are prohibited by law, in no event shall the company nor its respective directors, officers, employees, agents, service providers, contractors, licensors, licensees, suppliers, or successors be liable under these terms of service to you or any third-party for any consequential, indirect, incidental, exemplary, special, or punitive damages whatsoever, including any damages for business interruption, loss of use, data, revenue or profit, cost of capital, loss of business opportunity, loss of goodwill, whether arising out of breach of contract, tort (including negligence), any other theory of liability, or otherwise, regardless of whether such damages were foreseeable and whether or not the company was advised of the possibility of such damages.

    Indemnification

    To the maximum extent permitted by applicable law, you agree to defend, indemnify, and hold harmless Company, its parent, subsidiaries, affiliates, and their respective directors, officers, employees, agents, service providers, contractors, licensors, suppliers, successors, and assigns from and against any claims, liabilities, damages, judgments, awards, losses, costs, expenses, or fees (including reasonable attorneys' fees) arising out of or relating to your breach of these Terms of Service or your use of the Website including, but not limited to, third-party sites and content, any use of the Website's content and services other than as expressly authorized in these Terms of Service or any use of any goods, digital products and information purchased from this Website.

    Dispute Resolution

    At Company’s sole discretion, it may require you to submit any disputes arising from these Terms of Service or use of the Website, including disputes arising from or concerning their interpretation, violation, invalidity, non-performance, or termination, to final and binding arbitration under the Rules of Arbitration of the American Arbitration Association applying Ontario law. (If multiple jurisdictions, under applicable laws).

    Any cause of action or claim you may have arising out of or relating to these terms of use or the website must be commenced within 1 year(s) after the cause of action accrues; otherwise, such cause of action or claim is permanently barred.

    Privacy Policy

    Your provision of personal information through the Website is governed by our privacy policy located at the "Privacy Policy".

    Governing Law

    The Website and these Terms of Service will be governed by and construed in accordance with the laws of the Province of Ontario and any applicable federal laws applicable therein, without giving effect to any choice or conflict of law provision, principle, or rule and notwithstanding your domicile, residence, or physical location. Any action or proceeding arising out of or relating to this Website and/or under these Terms of Service will be instituted in the courts of the Province of Ontario, and each party irrevocably submits to the exclusive jurisdiction of such courts in any such action or proceeding. You waive any and all objections to the exercise of jurisdiction over you by such courts and to the venue of such courts.

    If you are a citizen of any European Union country or Switzerland, Norway or Iceland, the governing law and forum shall be the laws and courts of your usual place of residence.

    The parties agree that the United Nations Convention on Contracts for the International Sale of Goods will not govern these Terms of Service or the rights and obligations of the parties under these Terms of Service.

    Severability

    If any provision of these Terms of Service is illegal or unenforceable under applicable law, the remainder of the provision will be amended to achieve as closely as possible the effect of the original term and all other provisions of these Terms of Service will continue in full force and effect.

    Entire Terms of Service

    These Terms of Service constitute the entire and only Terms of Service between the parties in relation to its subject matter and replaces and extinguishes all prior or simultaneous Terms of Services, undertakings, arrangements, understandings or statements of any nature made by the parties or any of them whether oral or written (and, if written, whether or not in draft form) with respect to such subject matter. Each of the parties acknowledges that they are not relying on any statements, warranties or representations given or made by any of them in relation to the subject matter of these Terms of Service, save those expressly set out in these Terms of Service, and that they shall have no rights or remedies with respect to such subject matter otherwise than under these Terms of Service save to the extent that they arise out of the fraud or fraudulent misrepresentation of another party. No variation of these Terms of Service shall be effective unless it is in writing and signed by or on behalf of Company.

    Waiver

    No failure to exercise, and no delay in exercising, on the part of either party, any right or any power hereunder shall operate as a waiver thereof, nor shall any single or partial exercise of any right or power hereunder preclude further exercise of that or any other right hereunder.

    Notice

    We may provide any notice to you under these Terms of Service by: (i) sending a message to the email address you provide to us and consent to us using; or (ii) by posting to the Website. Notices sent by email will be effective when we send the email and notices we provide by posting will be effective upon posting. It is your responsibility to keep your email address current.

    To give us notice under these Terms of Service, you must contact us as follows: (i) by personal delivery, overnight courier or registered or certified mail to Scry Analytics Inc. 2635 North 1st Street, Suite 200 San Jose, CA 95134, USA. We may update the address for notices to us by posting a notice on this Website. Notices provided by personal delivery will be effective immediately once personally received by an authorized representative of Company. Notices provided by overnight courier or registered or certified mail will be effective once received and where confirmation has been provided to evidence the receipt of the notice.

    Contact Us

    To request a copy for your information, unsubscribe from our email list, request for your data to be deleted, or ask a question about your data privacy, we've made the process simple:

    Email us