Borealis
All stakeholder engagement activities can be managed from one platform. Additional modules can be added to strengthen governance, environment, and social areas. Borealis' Stakeholder Engagement module gives you the tools to create more effective engagement plans, strengthen relationships with stakeholders, and align processes with industry best practice. To simplify your day, the Stakeholder Engagement module centralizes all stakeholder information and makes it easily accessible.
Build stakeholder trust with a proven methodology
Plan
Connect engagement strategy to execution. The mapping tool in Borealis makes it easy to analyze stakeholders to prioritize the allocation of resources.
Engage
Communicate with stakeholders in a more relevant and timely manner. Borealis uses AI-driven machine learning to keep records clean and up-to-date.
Measure
Prove compliance with ever-evolving standards. Borealis lets you easily track and progress, generate reports and documentation, and demonstrate the impacts of your efforts.
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Qloo
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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AeroGCS
AeroGCS is a sophisticated Ground Control Station (GCS) software created by AeroMegh, aimed at optimizing the planning and execution of drone missions with precision and efficiency. This software encompasses comprehensive support for various aspects of drone flight control, automation of missions, and data collection. Users can formulate intricate flight plans, oversee drone fleets, and adhere to necessary regulatory requirements. AeroGCS is available in several editions, each specifically designed for unique applications, including precision agriculture, drone surveying, and extensive fleet management. The platform is equipped with a user-friendly interface, real-time flight monitoring, and smooth cloud integration, making it an invaluable resource for sectors such as agriculture, construction, defense, and environmental monitoring. By improving mission planning and operational processes, AeroGCS boosts efficiency and accuracy, ultimately increasing productivity in drone-related initiatives. Furthermore, its versatility allows users to adapt the software to various operational needs, further enhancing its appeal across diverse industries.
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Google Earth Engine
Google Earth Engine serves as a cloud-centric platform designed for the scientific examination and visualization of geospatial data, granting users access to an extensive public archive containing over 90 petabytes of analysis-ready satellite imagery alongside more than 1,000 carefully curated geospatial datasets. This rich collection boasts over five decades of historical imagery that is refreshed daily, with pixel resolutions reaching as fine as one meter, showcasing datasets from sources such as Landsat, MODIS, Sentinel, and the National Agriculture Imagery Program (NAIP). Through its web-based JavaScript Code Editor and Python API, Earth Engine empowers users to perform analyses on Earth observation data while employing machine learning techniques, thereby enabling the creation of sophisticated geospatial workflows. The platform's seamless integration with Google Cloud facilitates large-scale parallel processing, allowing for thorough analyses and efficient visualization of Earth data. Furthermore, Earth Engine's compatibility with BigQuery enhances its capabilities, making it a versatile tool for users in various fields. This unique combination of features positions Google Earth Engine as an essential resource for researchers and professionals working with geospatial information.
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