


- Description
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FindGrant.ca uses AI to help find government grants for women, Indigenous, BIPOC, SME and startups to research, hire and expand.
Our mission is to simplify the grant application process by using advanced AI-powered tools to match users with relevant funding programs across various sectors. - Number of employees
- 2 - 10 employees
- Company website
- https://FindGrant.ca
- Industries
- It & computing Technology
- Representation
- Minority-Owned Women-Owned Community-Focused
Socials
Recent projects
Website Development for FindGrant
We would like to work with students to develop a new website that is easy to maintain while providing an appealing interface for users. This can be achieved through modern site building tools with e.g. Expo, Javascript and HTML This will involve several different steps for the students, including: Building a website, with our assistance in providing the content and guidance. Providing training on updating and maintaining the website. Bonus steps in the process would also include: Testing prototypes with customers and refining ideas with feedback.
Grant Opportunities Dashboard
FindGrant aims to enhance its ability to track and analyze grant opportunities across Canada by developing a comprehensive data dashboard. The project involves creating a user-friendly interface that allows users to drill down into grant data by location, industry, grant use, and ethnicity. This dashboard will serve as a valuable tool for organizations and individuals seeking funding opportunities, enabling them to make informed decisions based on specific criteria. The project will require learners to apply their skills in data visualization, user interface design, and data analysis. Key tasks include: - Designing a user-friendly dashboard interface. - Integrating data sources related to Canadian grants. - Implementing drill-down features for detailed analysis.
AI-Powered Grant Proposal Assistant
FindGrant aims to streamline the grant proposal writing process by developing an AI-powered tool that assists users in crafting compelling and effective grant proposals. The project involves creating a prototype of an AI tool that can analyze grant requirements, suggest relevant content, and provide feedback on proposal drafts. The tool should leverage natural language processing (NLP) to understand and generate human-like text, making it easier for users to articulate their ideas clearly and persuasively. The goal is to reduce the time and effort required in writing grant proposals while increasing the chances of success. The project will focus on integrating AI capabilities with user-friendly interfaces to ensure accessibility for users with varying levels of technical expertise. Key tasks include: - Researching existing AI tools and techniques for natural language processing. - Designing a user interface that is intuitive and easy to navigate. - Developing algorithms that can analyze and generate text based on grant requirements. - Testing the prototype with sample grant proposals to evaluate its effectiveness.
Smart Grant Recommendation Engine
FindGrant is seeking to enhance its platform by integrating a Smart Recommendation Engine that can suggest relevant grants to users based on their profiles and past grants success data. The goal is to improve user experience by providing personalized grant suggestions, thereby increasing user engagement and satisfaction. This project involves developing an algorithm that analyzes user data, such as interests, previous grant applications, and success rates, to generate tailored recommendations. The engine should be capable of learning and adapting over time to improve its accuracy. Learners will apply their knowledge of data analysis, machine learning, and software development to create a prototype of this recommendation system. The project will focus on creating a scalable and efficient solution that can be integrated into the existing FindGrant platform. - Analyze user data to identify key factors for grant recommendations. - Develop a machine learning model to predict relevant grants for users. - Ensure the recommendation engine is scalable and efficient. - Test and validate the engine's accuracy and adaptability.
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