Gramener, in association with Microsoft have been offering solutions to customers across different domains, globally, ranging from point solutions like clustering to advanced analytics solutions using AI, ML, and Deep Learning models.
The objective of the partnership is to build solutions on the top of Microsoft Stack to help organizations decode big data easily.
With the motto of Data Science for Good, the teams collaboratively work with state-of-the-art techniques in areas such as computer vision, geo satellite analytics, natural language processing, and data storytelling.
AI for Earth is a Microsoft initiative that supports, and partners with environmental groups and researchers to tackle some of the world’s most intractable problems by marshalling the immense power of AI and ML.
Gramener contributes by developing AI-driven APIs and models to help researchers crunch big data easily and find actionable insights.
Leveraging the software and platform offerings from Microsoft we consult and work across diverse public sector stakeholders including Govt., NGO’s, Field force.
The visual analytics solutions are helping Indian and Singapore Govt. analyze progress and efficacy of health, nutrition, sanitation, agriculture and many more programs across geographies. Our AI labs team leverages AI and its allies to help public and civic sectors strengthen communities.
Microsoft’s corporate mission is “to empower every person and every organization on the planet to achieve more.” This mission statement shows that the business is all about empowerment of people and organizations. Such empowerment is achieved through the utility of the company’s computing products.
Gramener builds data applications and visual analytics applications to empower Microsoft Products such as PowerBI unleash it’s full potential.
With the Drilldown Choropleth, you can explore deep geographic data, plotting hundreds or even thousands of items (all US counties and precincts at once) and then drilling down their data hierarchy.
The Drilldown Cartogram visuals display a hierarchical map set as a circle for each location, with size/color from specified values.
Earlier biologists would manually identify and record fish species. Now deep learning AI models enable automatic fish detection saving time, human resource, and cost.
Using this API you can count any number of objects in the crowd. The application ML-driven and generates heatmaps for the crowd extracting an exact count of objects in the crowd.
This penguin dataset is a collection of images of penguin colonies in Antarctica coming from the larger penguin watch project, which was set up with the purpose of monitoring their changes in population.
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