- Description
-
Vici AI is an all-in-one AI-powered platform that makes gut health services affordable, accessible, and scalable by assisting alternative health professionals in their workflows.
- Number of employees
- 2 - 10 employees
- Company website
- https://getvici.ca
- Categories
- Software development Machine learning Artificial intelligence Public health Education
- Industries
- Business services Hospital, health, wellness & medical Technology
Socials
Recent projects
Website and App Development for Vici AI Inc.
Project Overview Vici AI Inc. aims to develop a fully functional prototype web app & website that integrates its proprietary AI models to enhance productivity and reduce complexity in creating work materials for clients. This project combines frontend, backend, and data annotation tasks to achieve the main goal. Main Goals Develop a fully functional prototype web app that integrates Vici AI Inc.'s proprietary AI models Enhance productivity and reduce complexity in creating work materials for clients (diet plans, health overviews, meeting notes, knowledge transfer documents, etc.) Provide high-quality training data to improve the performance of Vici AI Inc.'s machine learning models Learning Opportunities Frontend development (Figma design implementation, UI/UX design principles, intuitive UI/UX design, color theory, design best practices) Backend development (API design, database integration, server-side logic, AI model integration, data processing, API security) Data annotation techniques (high-quality training data, data labeling, tagging, categorization) Application Options Applicants can choose to work on a single aspect of the project. Please specify your preferred aspect in your application: Frontend Development : Focus on developing the user interface and user experience of the web app and website. Backend Development : Concentrate on building the server-side logic, API integration, and data processing. Data Annotation : Specialize in annotating data to provide high-quality training data for Vici AI Inc.'s machine learning models.
Social Media Marketing Strategy for Vici AI Inc.
Vici AI Inc. is looking to enhance its online presence and engage more effectively with its audience through social media platforms. The goal of this project is to develop a comprehensive social media marketing strategy that will help the company create engaging content, edit videos, and grow its follower base. The project will involve analyzing current social media trends, identifying the target audience, and crafting a content calendar that aligns with Vici AI Inc.'s brand values and objectives. The team will also be responsible for creating sample content, including graphics and short videos, to demonstrate the proposed strategy. This project provides an excellent opportunity for learners to apply their knowledge of digital marketing, content creation, and social media analytics.
Frontend Development for Vici AI Inc.
Vici AI Inc. Β develop a fully functional prototype web app Β that integrates Vici AI Inc.'s proprietary AI models to enhance productivity and reduce complexity in creating work materials for clients. Work materials including but not limited to: Diet plans Health overviews Meeting notes Knowledge transfer documents Learning Opportunities: Apply knowledge of frontend development, Figma design implementation, and UI/UX design principles Develop skills in intuitive UI/UX design, color theory, and design best practices Analyze stakeholder management and effective communication strategies
High-Quality Data Annotation for Machine Learning Models
Vici AI Inc. is focused on enhancing the performance of its machine learning models by leveraging high-quality training data. The goal of this project is to provide learners with an opportunity to apply their knowledge of data annotation techniques to real-world datasets. The project involves annotating a given dataset with relevant labels, tags, and categories to ensure accuracy and consistency. This will help improve the performance of Vici AI Inc.'s machine learning models by providing them with well-annotated training data. The tasks are closely related and can be completed by a team of learners specializing in data science or a related field. The project is designed to be completed within 100 hours.